We apologize if you receive multiple copies of this notice.
-----------------------------------------------------------------------------
ScalA’17: 8th Workshop on Latest Advances in
Scalable Algorithms for Large-Scale Systems
held in conjunction with the
SC17: The International Conference on High Performance
Computing, Networking, Storage and Analysis
in cooperation with ACM SIGHPC
November 13, 2017, Denver, CO, USA
<http://www.csm.ornl.gov/srt/conferences/Scala/2017>
Novel scalable scientific algorithms are needed in order to enable key
science applications to exploit the computational power of large-scale
systems. This is especially true for the current tier of leading petascale
machines and the road to exascale computing as HPC systems continue to scale
up in compute node and processor core count. These extreme-scale systems
require novel scientific algorithms to hide network and memory latency, have
very high computation/communication overlap, have minimal communication, and
have no synchronization points.
Scientific algorithms for multi-petaflop and exa-flop systems also need to be
fault tolerant and fault resilient, since the probability of faults increases
with scale. Resilience at the system software and at the algorithmic level is
needed as a crosscutting effort. Finally, with the advent of heterogeneous
compute nodes that employ standard processors as well as GPGPUs, scientific
algorithms need to match these architectures to extract the most performance.
This includes different system-specific levels of parallelism as well as
co-scheduling of computation. Key science applications require novel
mathematical models and system software that address the scalability and
resilience challenges of current- and future-generation extreme-scale HPC
systems.
Submission Guidelines
Authors are invited to submit manuscripts in English structured as technical
papers not exceeding 8 letter size (8.5in x 11in) pages including figures,
tables, and references using the ACM format for conference proceedings.
Submissions not conforming to these guidelines may be returned without
review. Reference style files are available at
<http://www.acm.org/sigs/publications/proceedings-templates>.
All manuscripts will be reviewed and judged on correctness, originality,
technical strength, and significance, quality of presentation, and interest
and relevance to the workshop attendees. Submitted papers must represent
original unpublished research that is not currently under review for any
other conference or journal. Papers not following these guidelines will be
rejected without review and further action may be taken, including (but not
limited to) notifications sent to the heads of the institutions of the
authors and sponsors of the conference. Submissions received after the due
date, exceeding length limit, or not appropriately structured may also not
be considered. At least one author of an accepted paper must register for
and attend the workshop. Authors may contact the workshop program chair for
more information. Papers should be submitted electronically at:
<https://easychair.org/conferences/?conf=scala17>.
Full papers will be published with the SC'17 workshop proceedings in the ACM
Digital Library and IEEE Xplore. Selected papers will be invited for an
extended version in a special issue of the Journal of Computational Science
(JoCS).
Important Dates
- Full paper submission: August 28, 2017
- Notification of acceptance: September 11, 2017
- Final paper submission (firm): October 9, 2017
- Workshop/conference early registration: TBD
- Workshop: November 13, 2017
Topics of interest include, but are not limited to:
- Novel scientific algorithms that improve performance, scalability,
resilience, and power efficiency
- Porting scientific algorithms and applications to many-core and
heterogeneous architectures
- Performance and resilience limitations of scientific algorithms and
applications at scale
- Crosscutting approaches (system software and applications) in addressing
scalability challenges
- Scientific algorithms that can exploit extreme concurrency (e.g. 1 billion
for exascale by 2020)
- Naturally fault tolerant, self-healing, or fault oblivious scientific
algorithms
- Programming model and system software support for algorithm scalability and
resilience
Workshop Chairs
- Vassil Alexandrov, Barcelona Supercomputing Center, Spain
- Al Geist, Oak Ridge National Laboratory, USA
- Jack Dongarra, University of Tennessee, Knoxville, USA
Workshop Program Chair
- Christian Engelmann, Oak Ridge National Laboratory, USA
Program Committee
- Vassil Alexandrov, Barcelona Supercomputing Center, Spain
- Hartwig Anzt, University of Tennessee, Knoxville, USA
- Rick Archibald, Oak Ridge National Laboratory, USA
- Franck Cappello, Argonne National Laboratory and
University of Illinois at Urbana Champaign, USA
- Zizhong Chen, University of California, Riverside, USA
- James Elliott, Sandia National Laboratories, USA
- Nahid Emad, University of Versailles SQ, France
- Christian Engelmann, Oak Ridge National Laboratory, USA
- Wilfried Gansterer, University of Vienna, Austria
- Michael Heroux, Sandia National Laboratories, USA
- Kirk E. Jordan, IBM T.J. Watson Research, USA
- Dieter Kranzlmueller, Ludwig-Maximilians-University Munich, Germany
- Ignacio Laguna, Lawrence Livermore National Laboratory, USA
- Piotr Luszczek, University of Tennessee, Knoxville, USA
- Michael Mascagni, Florida State University, USA
- Ron Perrot, University of Oxford, UK
- Yves Robert, ENS Lyon, France
- Stuart Slattery, Oak Ridge National Laboratory, USA
- Keita Teranishi, Sandia National Laboratories, USA
--
Christian Engelmann, Ph.D.
R&D Staff Scientist
Computer Science Research Group
Computer Science and Mathematics Division
Oak Ridge National Laboratory
Mail: P.O. Box 2008, Oak Ridge, TN 37831-6173, USA
Phone: +1 (865) 574-3132 / Fax: +1 (865) 576-5491
e-Mail: engelmannc(a)ornl.gov / Home: www.christian-engelmann.info
[Please accept our apologies if you receive multiple copies of this CFP]
*The 10th International Conference on Current and Future Trends of
Information and Communication Technologies in Healthcare (ICTH)*
*Date*: November 2-5, 2020
*Location*: Madeira, Portugal
*Website*: http://cs-conferences.acadiau.ca/icth-20/
*Important Dates*---------------
- *Workshop Proposals*: May 30, 2020
- *Paper Submission Due*: June 15, 2020
- *Author Notification*: August 2, 2020
- *Final Manuscript Due*: August 30, 2020
*Publication*
-----------
All ICTH 2020 accepted papers will be published by Elsevier Science in the
open-access Procedia Computer Science series on-line. Procedia Computer
Science is hosted by Elsevier on www.Elsevier.com
<http://www.elsevier.com/> and
on Elsevier content platform ScienceDirect (www.sciencedirect.com), and
will be freely available worldwide. All papers in Procedia will be indexed
by Scopus (www.scopus.com) and by Thomson Reuters' Conference Proceeding
Citation Index (
http://thomsonreuters.com/conference-proceedings-citation-index/). All
papers in Procedia will also be indexed by Scopus (www.scopus.com) and
Engineering Village (Ei) (www.engineeringvillage.com). This includes EI
Compendex (www.ei.org/compendex). Moreover, all accepted papers will be
indexed in DBLP (http://dblp.uni-trier.de/). The papers will contain linked
references, XML versions and citable DOI numbers. Selected papers will be
invited for publication, in the special issues of:
- International Journal of Ambient Intelligence and Humanized
Computing (IF: 1.901), by Springer (
http://www.springer.com/engineering/journal/12652)
- International Journal of Computing and Informatics (IF: 0.524), (
http://www.cai.sk/ojs/index.php/cai/index)
- International Journal of E-Health and Medical Communications, by IGI
Global: (
http://www.igi-global.com/journal/international-journal-health-medical-comm…
)
ICTH 2020 will be held in conjunction with the 11th International
Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSN:
http://cs-conferences.acadiau.ca/euspn-20/). Papers on either completed or
ongoing research are invited:
http://cs-conferences.acadiau.ca/icth-20/call-for-papers.html
ICTH 2020 will be held in Madeira, a Portuguese archipelago. Madeira is a
popular year-round tourist destination, known for its remarkable
mountainous scenery and mild year-long climate. Although, Madeira is part
of Europe it is approximately 1,000 km from the continent while being only
520 km from the coast of Africa. It is about an hour and a half flight from
the capital of Portugal, Lisbon. Funchal, the picturesque capital of
Madeira, is situated on the south coast of the island and one of Atlantic
Oceans most popular cruise ship ports. Madeira is a scenic island with many
unique destinations such as the Laurisilva forest, a UNESCO World Heritage
site.
*Topics of interest include, but are not limited to*:
-------------------------------------------
- Ambient Assisted Living for Elderly Care
- Ambient Intelligence and Intelligent Service Systems
- Analysis and Evaluation of Healthcare Systems
- Clinical Data and Knowledge Management
- Cloud Computing for Healthcare
- Collaboration Technologies for Healthcare
- Context-aware Applications for Patient Monitoring and Care
- Data mining Techniques and Data Warehouses in Healthcare
- Data Visualization
- Decision Support Systems in Healthcare
- Design and Development Methodologies for Healthcare Systems
- Diagnostic and Therapeutic Technologies in Healthcare
- Digital Hospitals
- Drug Information Systems
- E-health & m-health
- Electronic Health Records (EHR) & Personal Health Records (PHR)
- Evidence Based Medicine (EBM)
- Healthgrids
- Health Portals
- Information and Knowledge Processing in Healthcare Environments
- Middleware Support for Smart Homes and Intelligent Applications
- Quantified Self for Pervasive Healthcare
- Privacy, Confidentiality and Security Issues in Healthcare Systems
- Related Real World Experimentations and Case Studies in Healthcare
- RFID Solutions for Healthcare
- Smart Homes and Home Care Intelligent Environments
- Telemedicine and Health Telematics
- Ubiquitous and Pervasive Computing in Healthcare
- Usability & Socio Technical studies
- User Interface Design for Healthcare Applications
- Virtual and Augmented Reality in Healthcare
- Virtual Environments for Healthcare
*Committees*
----------
General Chairs
Heiko Gewald, The Neu-Ulm University of Applied, Germany
Joel J. P. C. Rodrigues, National Institute of Telecommunications
(Inatel), Brazil
Program Chairs
Stéphane Galland, Université de Technologie de Belfort-Montbéliard, France
Nuno Varandas, F6S (Where Founders Grow Together), Portugal
Local Arrangements Chairs
Rui Neves Madeira, Polytechnic Institute of Setúbal, Portugal
Nelson Rocha, University of Aveiro, Portugal
Workshops Chair
Haroon Malik, Marshall University, USA
International Journals Chair
Bin Guo, Northwestern Polytechnical University, China
Publicity Chairs
Sony Guntuka, Acadia University, Canada
Mohammed Fattah, Moulay Ismail University, Morocco
Technical Program Committee
http://cs-conferences.acadiau.ca/icth-20/program-committees.html
Steering Committee Chair
Elhadi Shakshuki, Acadia University, Canada
Advisory Committee
Abdullah Ali Al-Maniri, Oman Medical Specialty Board, Oman
Sergio Camorlinga, Head eHealth Research, TRLabs, Canada
Kevin Daimi, University of Detroit Mercy, USA
Finn Kensing, University of Copenhagen, Denmark
Francesco Princiroli, Politecnico di Milano, Italy
Abdul Roudsari, University of Victoria, Canada
We apologize if you receive multiple copies of this call for papers.
--------------------------------------------------------------------------------
13th Workshop on Resiliency in High Performance Computing (Resilience)
in Clusters, Clouds, and Grids
<https://www.csm.ornl.gov/srt/conferences/Resilience/2020>
in conjunction with
the 26th International European Conference on Parallel and Distributed
Computing (Euro-Par), Warsaw, Poland
August 24 - 28, 2020
<http://2020.euro-par.org>
2020 Workshop Format:
Due to the exceptional situation of COVID-19, this year Euro-Par and its workshops will be organized as an all-virtual event. This includes the main conference and workshops. The accepted workshop papers must be presented by one of the authors in order to be included in the proceedings. There will be a single minimal registration fee for each accepted paper in order to cover expenses associated with organization and proceedings publication. Lastly, the preferred presentation format for the workshop will be via a streaming presentation, with slides and pre-recorded video presentations used in exceptional situations.
Overview:
Resilience is a critical challenge as high performance computing (HPC) systems continue to increase component counts, individual component reliability decreases (such as due to shrinking process technology and near-threshold voltage (NTV) operation), hardware complexity increases (such as due to heterogeneous computing) and software complexity increases (such as due to complex data- and workflows, real-time requirements and integration of artificial intelligence (AI) technologies with traditional applications).
Correctness and execution efficiency, in spite of faults, errors, and failures, is essential to ensure the success of the HPC systems, cluster computing environments, Grid computing infrastructures, and Cloud computing services. The impact of faults, errors, and failures in such HPC systems can range from financial losses due to system downtime (sometimes several tens-of-thousands of Dollars per lost system-hour), to financial losses due to unnecessary overprovision (acquisition and operating costs), to financial losses and legal liabilities due to erroneous or delayed output.
The emergence of AI technology opens up new possibilities, but also new problems. Using AI technology for operational intelligence that enables resilience in HPC systems and centers is a complex control problem, while designing resilient AI technology for HPC applications is a difficult algorithmic problem. Resilience for HPC systems encompasses a wide spectrum of fundamental and applied research and development, including theoretical foundations, error/failure and anomaly detection, monitoring and control, end-to-end data integrity, enabling infrastructure, and resilient algorithms.
This workshop brings together experts in the community to further research and development in HPC resilience and to facilitate exchanges across the computational paradigms of extreme-scale HPC, cluster computing, Grid computing, and Cloud computing.
Submission Guidelines:
Authors are invited to submit papers electronically in English in PDF format. Submitted manuscripts should be structured as technical papers and BETWEEN 10 AND 12 PAGES, including figures, tables and references, using Springer's Lecture Notes in Computer Science (LNCS) format at <http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>. Papers with less than 10 or more than 12 pages will not be accepted due to publisher guidelines. Submissions should include abstract, key words and the e-mail address of the corresponding author. Papers not conforming to these guidelines may be returned without review. All manuscripts will be reviewed and will be judged on correctness, originality, technical strength, significance, quality of presentation, and interest and relevance to the conference attendees. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected
without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date or not appropriately structured may also not be considered. The proceedings will be published in Springer's LNCS as post-conference proceedings. At least one author of an accepted paper must register for and attend the workshop for inclusion in the proceedings. Authors may contact the workshop program chairs for more information.
Important websites:
- Resilience 2020 Website: <https://www.csm.ornl.gov/srt/conferences/Resilience/2020>
- Resilience 2020 Submissions: <https://easychair.org/conferences/?conf=europar2020workshop>
- Euro-Par 2020 website: <http://2020.euro-par.org>
Topics of interest include, but are not limited to:
- Theoretical foundations for resilience:
- Metrics and measurement
- Statistics and optimization
- Simulation and emulation
- Formal methods
- Efficiency modeling and uncertainty quantification
- Experience reports
- Error/failure/anomaly detection and reliability/dependability modeling:
- Statistical analyses
- Machine learning and artificial intelligence
- Digital twins
- Data collection and aggregation
- Information visualization
- Monitoring and control for resilience:
- Center, system and application monitoring and control
- Reliability, availability, serviceability and performability
- Tunable fidelity and quality of service
- Automated response and recovery
- Operational intelligence to enable resilience
- End-to-end integrity:
- Fault tolerant design of centers, systems and applications
- Forward migration and verification
- Degraded operation
- Error propagation, failure cascades, and error/failure containment
- Testing and evaluation, including fault/error/failure injection
- Enabling infrastructure for resilience:
- Reliability, availability, serviceability systems
- System software and middleware
- Resilience extensions for programming models
- Tools and frameworks
- Support for resilience in heterogeneous architectures
- Resilient algorithms:
- Algorithmic detection and correction
- Resilient solvers and algorithm-based fault tolerance
- Fault tolerant numerical methods
- Robust iterative algorithms
- Resilient artificial intelligence
Important Dates:
- Workshop papers due: May 29, 2020
- Workshop author notification: July 3, 2020
- Workshop author registration: TBA
- Workshop paper (for informal workshop proceedings): July 10, 2020
- Workshop date: August 24 or 25, 2020
- Workshop camera-ready papers: September 11, 2020 (after the conference)
General Co-Chairs:
- Stephen L. Scott
Tennessee Tech University, USA
scottsl(a)ornl.gov
- Christian Engelmann
Oak Ridge National Laboratory , USA
engelmannc(a)ornl.gov
Program Co-Chairs:
- Ferrol Aderholdt
Middle Tennessee State University, USA
ferrol.aderholdt(a)mtsu.edu
- Thomas Naughton
Oak Ridge National Laboratory , USA
naughtont(a)ornl.gov
Workshop Chair Emeritus
- Chokchai (Box) Leangsuksun
Louisiana Tech University, USA
box(a)latech.edu
_________________________________________________________________________
Thomas Naughton naughtont(a)ornl.gov
Research Associate (865) 576-4184
*The GraMSec submission deadline is extended to Monday, May 4.*
Please find below the full CFP.
======================================================================
GraMSec 2020: The Seventh International Workshop on Graphical Models for
Security
http://gramsec.uni.lu
June 22, 2020 *Online event*
Co-located with CSF 2020
*LNCS post-proceedings confirmed*
SCOPE
The use of graphical security models to represent and analyse the
security of systems has gained an increasing research attention over the
last two decades. Formal methods and computer security researchers, as
well as security professionals from the industry and government, have
proposed various graphical security models, metrics, and measurements.
Graphical models are used to capture different security facets and
address a range of challenges including security assessment, automated
defence, secure services composition, security policy validation, and
verification. The International Workshop on Graphical Models for Security
is an established scientific event dedicated to study and exchange
of experiences on graphical security and safety modelling.
TOPICS
This year, we encourage excellent submissions related, but not
restricted, to the following broad headings:
1. Graph representations: mathematical, conceptual, and implemented
tools for describing and reasoning about security and safety
2. Logical approaches: formal logical tools for representing and
reasoning about graphs and their use as modelling tools in security
3. Machine learning: modelling and reasoning about the role of big data
and machine learning in security operations
4. Networks in national security: terrorist networks, counter-terrorism
networks; safety in national infrastructure (e.g., utilities and
transportation)
5. Risk analysis and management: models and graphical methodologies for
security and privacy risk management in business and organisational
architectures
6. Social networks: using and reasoning about social graphs, network
analysis, network protocols, social mapping, sociometry.
7. Semantics: developing or studying semantic approaches to graph-based
models used in security like set theoretic models, categorical models,
logical models, etc.
8. Threat modelling: modelling and analysing software systems security,
models for DevSecOps, etc.
9. Security requirements: models and tools for describing and analysing
requirements on system security and privacy.
10. Visual security: modelling and analytics for security visualisations.
11. Secure systems: safe and secure system design, quantification of
security/safety, models for system security/safety evaluation.
We welcome a broad range of contributions: from theory to tools and
experience reports. Preference will be given to papers likely to
stimulate high-quality debate at the Workshop.
SUBMISSION GUIDELINES
We solicit two types of submissions:
- Regular papers (up to 18 pages, excluding the bibliography and
well-marked appendices) describing original and unpublished work within
the scope of the workshop.
- Short papers (up to 10 pages, excluding the bibliography and
well-marked appendices) describing original and unpublished work in
progress.
The reviewers are not required to read the appendices, so the papers
should be intelligible without them. All submissions must be prepared
using the LNCS style. Each paper will undergo a thorough review process.
Submissions should be made using the GraMSec 2020 EasyChair website:
https://easychair.org/conferences/?conf=gramsec2020.
PUBLICATION
As in previous editions, we the post-proceedings will be published
in the Lecture Notes in Computer Science (LNCS) series,
published by Springer. Proceedings will be published after the
workshop, thus permitting the authors to incorporate feedback.
VENUE
Due to the current coronavirus outbreak, the IEEE CSF Symposium
and its associated workshops, including GraMSec, will be held
online this year. Details about registration and participation will
be soon made available.
IMPORTANT DATES
Given the situation and the fact that the workshop will be held online,
we will keep only one submission deadline.
- Paper submissions due: Monday, May 4, 2020
- Notifications: Friday, May 29, 2020
- Workshop: Monday, June 22, 2020
- Camera ready versions due: Friday, August 7, 2020
PROGRAM CHAIRS
Harley Eades III, Augusta University, United States of America
Olga Gadyatskaya, Leiden Institute of Advanced Computer Science,
Leiden University, The Netherlands
STEERING COMMITTEE
Sushil Jajodia, George Mason University, United States of America
Barbara Fila, INSA Rennes, IRISA, France
Sjouke Mauw, University of Luxembourg, Luxembourg
Christian W. Probst, Unitec, New Zealand
Ketil Stølen, SINTEF Digital and University of Oslo, Norway
PUBLICITY CHAIR
Barbara Fila, INSA Rennes, IRISA, France
WEB CHAIR
Reynaldo Gil Pons, University of Luxembourg, Luxembourg
[KDD Mining and Learning from Time Series 2020]: Call for papers
CFP Webpage: https://kdd-milets.github.io/milets2020/#call
--------------------------------------------------------------
KDD Mining and Learning from Time Series (MiLeTS) 2020
Aug 24th, 2020 - San Diego, California, USA
https://kdd-milets.github.io/milets2020/
--------------------------------------------------------------
----------------
KEY DATES
----------------
Paper Submission Deadline: May 20th, 2020, 11:59PM Alofi Time
Author Notification: June 15th, 2020
Camera Ready Version: July 2nd, 2020
Workshop: August 24th, 2020
--------------------------------------------------------------
MiLETS is the premier KDD workshop on Mining and Learning from Time Series.
Time series data are ubiquitous. In domains as diverse as finance,
entertainment, transportation, and health care, we observe a fundamental
shift away from parsimonious, infrequent measurement to nearly continuous
monitoring and recording. Rapid advances in diverse sensing technologies,
ranging from remote sensors to wearables and social sensing, are generating
rapid growth in the size and complexity of time series archives. Thus,
although time series analysis has been studied extensively, its importance
only continues to grow. What is more, modern time series data pose
significant challenges to existing techniques (e.g., irregular sampling in
hospital records and spatiotemporal structure in climate data). Finally,
time series mining research is challenging and rewarding because it bridges
a variety of disciplines and demands interdisciplinary solutions. Now is
the time to discuss the next generation of temporal mining algorithms. The
focus of MiLeTS workshop is to synergize the research in this area and
discuss both new and open problems in time series analysis and mining. The
solutions to these problems may be algorithmic, theoretical, statistical,
or systems-based in nature. Further, MiLeTS emphasizes applications to high
impact or relatively new domains, including but not limited to biology,
health and medicine, climate and weather, road traffic, astronomy, and
energy.
The MiLeTS workshop will discuss a broad variety of topics related to time
series, including:
· Time series pattern mining and detection, representation, searching
and indexing, classification, clustering, prediction, forecasting, and rule
mining.
· BIG time series data.
· Hardware acceleration techniques using GPUs, FPGAs and special
processors.
· Online, high-speed learning and mining from streaming time series.
· Uncertain time series mining.
· Privacy preserving time series mining and learning.
· Time series that are multivariate, high-dimensional, heterogeneous,
etc., or that possess other atypical properties.
· Time series with special structure: spatiotemporal (e.g., wind
patterns at different locations), relational (e.g., patients with similar
diseases), hierarchical, etc.
· Time series with sparse or irregular sampling, non-random missing
values, and special types of measurement noise or bias.
· Time series analysis using less traditional approaches, such as
deep learning and subspace clustering.
· Applications to high impact or relatively new time series domains,
such as health and medicine, road traffic, and air quality.
· New, open, or unsolved problems in time series analysis and mining.
------------------------------
Submission Guidelines
------------------------------
Submissions should follow the SIGKDD formatting requirements and will be
evaluated using the SIGKDD Research Track evaluation criteria. Preference
will be given to papers that are reproducible, and authors are encouraged
to share their data and code publicly whenever possible. Submissions are
strongly recommended to be no more than 4 pages, excluding references or
supplementary materials (all in a single pdf). The appropriateness of using
additional pages over the recommended length will be judged by reviewers.
All submissions must be in pdf format using the workshop template (latex,
word). Submissions will be managed via the MiLeTS 2020 EasyChair website.
*Note on open problem submissions:* To promote new and innovative research
on time series, we plan to accept a small number of high-quality
manuscripts describing open problems in time series analysis and mining.
Such papers should provide a clear, detailed description and analysis of a
new or open problem that poses a significant challenge to existing
techniques, as well as a thorough empirical investigation demonstrating
that current methods are insufficient.
*COVID-19 Time Series Analysis Special Track:* The COVID-19 pandemic is
impacting almost everyone worldwide and is expected to have life-altering
short and long-term effects. There are many potential applications of time
series analysis and mining that can contribute to the understanding of this
pandemic. We encourage the submission of high-quality manuscripts
describing original problems, time-series datasets, and novel solutions for
time series analysis and forecasting of COVID-19.
The review process is single-round and double-blind (submission files have
to be anonymized). Concurrent submissions to other journals and conferences
are acceptable. Accepted papers will be presented as posters during the
workshop and list on the website. Besides, a small number of accepted
papers will be selected to be presented as contributed talks.
Any questions may be directed to the workshop e-mail address:
kdd.milets(a)gmail.com.
-----------------
KEY DATES
-----------------
Paper Submission Deadline: May 20th, 2020, 11:59PM Alofi Time
Author Notification: June 15th, 2020
Camera Ready Version: July 2nd, 2020
Workshop: August 24th, 2020
-------------------------------
Organizing Committee
-------------------------------
Sanjay Purushotham
University of Maryland, Baltimore County
Yaguang Li
Google
--------------------------
Steering Committee
--------------------------
Eamonn Keogh
University of California Riverside
Yan Liu
University of Southern California
Abdullah Mueen
University of New Mexico
-------------
Contact:
--------------
Any questions may be directed to the workshop e-mail address:
kdd.milets(a)gmail.com.
**********************************************************************
We apologize if you received multiple copies of this Call for Papers
Please feel free to distribute it to those who might be interested
**********************************************************************
HiPC 2020 CALL FOR PAPERS
*********************************************************************
27th IEEE International Conference on High Performance Computing,
Data, and Analytics
16--19 December, 2020 in Pune India
https://hipc.org/
PROGRAM CHAIRS
HPC: Bora Uçar, CNRS and ENS Lyon, France
Data Science: Gagan Agrawal, Augusta University, USA
HPC TRACKS
Algorithms: Kamesh Madduri, Pennsylvania State University, USA
Applications: Yogesh Simmhan, Indian Institute of Science, India and
Ana Lucia Varbanescu, University of Amsterdam, The Netherlands
Architecture: Biswabandan Panda, IIT Kanpur, India
System Software: Marco Aldinucci, University of Torino, Italy
DATA SCIENCE TRACKS
Scalable Algorithms and Analytics: Bingsheng He, National University
of Singapore and Amelie Chi Zhou, Shenzhen University, China
Scalable Systems and Software: Suren Byna, Lawrence Berkeley National
Laboratory, USA
HiPC 2020 will be the 27th edition of the IEEE International
Conference on High Performance Computing, Data, Analytics and Data
Science. HiPC serves as a forum to present current work by researchers
from around the world as well as highlight activities in Asia in the
areas of high performance computing and data science. The meeting
focuses on all aspects of high performance computing systems, and data
science and analytics, and their scientific, engineering, and
commercial applications.
Authors are invited to submit original unpublished research
manuscripts that demonstrate current research in all areas of high
performance computing, and data science and analytics, covering all
traditional areas and emerging topics including from machine learning,
big data analytics and blockchain. Each submission should be
submitted to one of the tracks listed under the two broad themes of
High Performance Computing and Data Science.
Up to two best paper awards will be given for outstanding contributed papers.
HIGH PERFORMANCE COMPUTING
Algorithms. This track invites papers that describe original research
on developing new parallel and distributed computing algorithms, and
related advances. Examples of topics that are of interest include (but
not limited to):
* New parallel and distributed algorithms and design techniques;
* Advances in enhancing algorithmic properties or providing guarantees
(e.g., fault tolerance, resilience, concurrency, data locality,
communication-avoiding);
* Algorithmic techniques for resource allocation and optimization
(e.g., scheduling, load balancing, resource management);
* Provably efficient parallel and distributed algorithms for advanced
scientific computing and irregular applications (e.g., numerical
linear algebra, graph algorithms, computational biology);
* Classical and emerging computation models (e.g.,
parallel/distributed models, quantum computing, neuromorphic and other
bioinspired models).
Architecture. This track invites papers that describe original
research on the design and evaluation of high performance computing
architectures, and related advances. Examples of topics of interest
include (but not limited to):
* High performance processing architectures (e.g., reconfigurable,
system-on-chip, manycores, vector processors);
* Networks for high performance computing platforms (e.g.,
interconnect topologies, network-on-chip);
* Memory, cache and storage architectures (e.g., 3D, photonic,
Processing-In-Memory, NVRAM, burst buffers, parallel I/O);
* Approaches to improve architectural properties (e.g., energy/power
efficiency, reconfigurable, resilience/fault tolerance,
security/privacy);
* Emerging computational architectures (e.g., quantum computing,
neuromorphic and other bioinspired architectures).
Applications. This track invites papers that describe original
research on the design and implementation of scalable and high
performance applications for execution on parallel, distributed and
accelerated platforms, and related advances. Examples of topics of
interest include (but not limited to):
* Shared and distributed memory parallel applications (e.g.,
scientific computing, simulation and visualization applications, graph
and irregular applications, data-intensive applications,
science/engineering/industry applications, emerging applications in
IoT and life sciences, etc.);
* Methods, algorithms and optimizations for scaling applications on
peta- and exa-scale platforms (e.g., co-design of hardware and
software, heterogeneous and hybrid programming);
* Hardware acceleration of parallel applications (e.g., GPUs, FPGA,
vector processors, manycore);
* Application benchmarks and workloads for parallel and distributed platforms.
Systems Software. This track invites papers that describe original
research on the design, implementation and evaluation of systems
software for high performance computing platforms, and related
advances. Examples of topics of interest include (but not limited to):
* Scalable systems and software architectures for high performance
computing (e.g., middleware, operating systems, I/O services);
* Techniques to enhance parallel performance (e.g., compiler/runtime
optimization, learning from application traces, profiling);
* Techniques to enhance parallel application development and
productivity (e.g., Domain-Specific Languages, programming
environments, performance/correctness checking and debugging);
* Techniques to deal with uncertainties, hardware/software resilience,
and fault tolerance;
* Software for cloud, data center, and exascale platforms (e.g.,
middleware tools, schedulers, resource allocation, data migration,
load balancing);
* Software and programming paradigms for heterogeneous platforms
(e.g., libraries for CPU/GPU, multi-GPU clusters, and other
accelerator platforms).
DATA SCIENCE
Scalable Algorithms and Analytics. This track invites papers that
describe original research on developing scalable algorithms for data
analysis at scale, and related advances. Examples of topics of
interest include (but not limited to):
* New scalable algorithms for fundamental data analysis tasks
(supervised, unsupervised learning, and pattern discovery);
* Scalable algorithms that are designed to address the characteristics
of different data sources and settings (e.g., graphs, social networks,
sequences, data streams);
* Scalable algorithms and techniques to reduce complexity of
large-scale data (e.g., streaming, sublinear data structures,
summarization, compressive analytics);
* Scalable algorithms that are designed to address requirements in
different data-driven application domains (e.g., life sciences,
business, agriculture);
* Scalable algorithms that ensure the transparency and fairness of the analysis;
* Case studies, experimental studies and benchmarks for scalable
algorithms and analytics;
* Scaling and accelerating machine learning, deep learning and
computer vision applications.
Scalable Systems and Software. This track invites papers that describe
original research on developing scalable systems and software for
handling data at scale, and related advances. Examples of topics of
interest include (but not limited to):
* Design of scalable system software to support various applications
(e.g., recommendation systems, web search, crowdsourcing applications,
streaming applications)
* Scalable system software for various architectures (e.g., OpenPower,
GPUs, FPGAs).
* Architectures and systems software to support various operations in
large data frameworks (e.g., storage, retrieval, automated workflows,
data organization, visualization, visual analytics,
human-in-the-loop);
* Systems software for distributed data frameworks (e.g., distributed
file system, virtualization, cloud services, resource optimization,
scheduling);
* Standards and protocols for enhancing various aspects of data
analytics (e.g., open data standards, privacy preserving and secure
schemes).
IMPORTANT DATES (2020)
Abstract Submissions : June 8, 2020
Paper Submissions : June 15, 2020
Reviews for Rebuttals: August 4, 2020
Initial Submission Decisions: August 21, 2020
Revisions Due: September 22, 2020
Author Notifications: October 2, 2020
Camera Ready: October 16, 2020
Manuscript Guidelines
Submitted manuscripts should be structured as technical papers and may
not exceed ten (10) single-spaced double-column pages using 10-point
size font on 8.5x11 inch pages (IEEE conference style), including
figures, tables, and references. See style templates for details:
•LaTex Package (ZIP) – will be linked
•Word Package (ZIP) – will be linked
Electronic submissions must be in the form of a readable PDF file. All
manuscripts will be reviewed by the Program Committee and evaluated on
originality, relevance of the problem to the conference theme,
technical strength, rigor in analysis, quality of results, and
organization and clarity of presentation of the paper. Authors are
highly encouraged to list the key contributions of their paper, for
example in a separate paragraph in the introduction of the paper. The
review process is “single-blind” (i.e., authors can list their names
on the paper), and that there will be a rebuttal period.
Submitted papers must represent original unpublished research that is
not currently under review for any other conference or journal. Papers
not following these guidelines will be rejected without review and
further action may be taken, including (but not limited to)
notifications sent to the heads of the institutions of the authors and
sponsors of the conference. Submissions received after the due date,
exceeding length limit, or not appropriately structured may also not
be considered. Authors may contact the Program Chair at the email
address below for further information or clarification. A published
proceedings will be available at the conference.
At least one author of each paper must be registered for the
conference in order for the paper to be published in the proceedings.
Presentation of an accepted paper at the conference in person is a
requirement of publication. Any paper that is not presented at the
conference will not be included in IEEE Xplore.
Authors of selected high quality papers in HiPC 2020 will be invited
to submit extended versions of their papers for possible publication
in a special issue of Journal of Parallel and Distributed Computing.
Submit your paper: https://easychair.org/conferences/?conf=hipc2020.
__________________________________________________________________________
HiPC 2020 is co-sponsored by
* IEEE Computer Society Technical Committee on Parallel Processing (TCPP)
* HiPC Education Trust, India
In cooperation with:
* ACM Special Interest Group on Algorithms and Computation Theory (SIGACT);
* ACM Special Interest Group on Computer Architecture (SIGARCH);
* IFIP Working Group on Concurrent Systems;
* Manufacturers' Association for Information Technology (MAIT);
* National Association of Software and Service Companies (NASSCOM).
[apologies for cross-posting]
PRIVACY IN STATISTICAL DATABASES 2020 (PSD 2020)
================================================
Arezzo, Italy, Sep. 23-25, 2020
http://unescoprivacychair.urv.cat/psd2020
Submission deadline: **MAY 24, 2020**
** In spite of Covid-19, we plan to organize PSD 2020
as scheduled. The submission deadline (May 24, 2020)
stays valid **
1. AIMS AND GOAL
-----------------
Privacy in statistical databases is about finding trade-offs to the
tension between the increasing societal and economical demand for
accurate information and the legal and ethical obligation to protect
the privacy of individuals and enterprises which are the respondents
providing the statistical data. In the case of statistical databases,
the motivation for respondent privacy is one of survival: statistical
agencies or survey institutes cannot expect to collect accurate
information from individual or corporate respondents unless these feel
the privacy of their responses is guaranteed.
Beyond respondent privacy, there are two additional privacy dimensions
to be considered: privacy for the data owners (organizations owning or
gathering the data, who would not like to share the data they have
collected at great expense) and privacy for the users (those who
submit queries to the database and would like their analyses to stay
private).
"Privacy in Statistical Databases 2020" (PSD 2020) is a conference
sponsored and organized by the UNESCO Chair in Data Privacy
(http://unescoprivacychair.urv.cat) with proceedings published by
Springer-Verlag in Lecture Notes in Computer Science. The purpose of
PSD 2020 is to attract world-wide, high-level research in statistical
database privacy.
PSD 2020 is a successor to
- PSD 2018 (Valencia, Sep. 26-28, 2018,
https://unescoprivacychair.urv.cat/psd2018/),
- PSD 2016 (Dubrovnik, Sep. 14-16, 2016,
https://unescoprivacychair.urv.cat/psd2016/),
- PSD 2014 (Eivissa, Sep. 17-19, 2014,
http://unescoprivacychair.urv.cat/psd2014/),
- PSD 2012 (Palermo, Sep. 26-28, 2012,
http://unescoprivacychair.urv.cat/psd2012),
- PSD 2010 (Corfu, Sep. 22-24, 2010,
http://unescoprivacychair.urv.cat/psd2010),
- PSD 2008 (Istanbul, Sep. 24-26, 2008,
http://unescoprivacychair.urv.cat/psd2008),
- PSD 2006 (Rome, Dec. 13-15, 2006,
http://crises-deim.urv.cat/psd2006)
and PSD 2004 (Barcelona, June 9-11, 2004,
http://crises-deim.urv.cat/psd2004),
all with proceedings published by Springer in LNCS 11126, LNCS 9867,
LNCS 8744, LNCS 7556, LNCS 6344, LNCS 5262, LNCS 4302 and LNCS 3050,
respectively. Those nine PSD conferences follow a tradition of
high-quality technical conferences on SDC which started with
"Statistical Data Protection-SDP'98", held in Lisbon in 1998 and with
proceedings published by OPOCE, and continued with the AMRADS project
SDC Workshop, held in Luxemburg in 2001 and with proceedings published
in Springer LNCS 2316.
Like the aforementioned preceding conferences, PSD 2020 originates in
Europe, but wishes to stay a worldwide event in database privacy and
SDC. Thus, contributions and attendees from overseas are welcome.
2. ORGANIZATION
---------------
PROGRAM COMMITTEE (More members to be confirmed soon)
- Jane Bambauer (University of Arizona, USA)
- Bettina Berendt (Katholieke Universiteit Leuven, Belgium)
- Elisa Bertino (CERIAS, Purdue University, USA)
- Aleksandra Bujnowska (EUROSTAT, European Union)
- Jordi Castro (Universitat PolitËcnica de Catalunya)
- Anne-Sophie Charest (UniversitÈ Laval, QuÈbec, Canada)
- Chris Clifton (Purdue University, USA)
- Graham Cormode (University of Warwick, UK)
- Peter-Paul de Wolf (Statistics Netherlands)
- Josep Domingo (Universitat Rovira i Virgili, Catalonia)
- Joerg Drechsler (IAB, Germany)
- Khaled El Emam (University of Ottawa, Canada)
- Mark Elliot (Manchester University, UK)
- SÈbastien Gambs (UniversitÈ du QuÈbec ‡ MontrÈal)
- Sarah Giessing (Destatis, Germany)
- Hiroaki Kikuchi (Meiji University, Japan)
- Bradley Malin (Vanderbilt University, USA)
- Laura McKenna (Census Bureau, USA)
- Anna Monreale (Universit‡ di Pisa, Italy)
- Krish Muralidhar (The University of Oklahoma, USA)
- Anna Oganyan (National Center for Health Statistics, USA)
- David Rebollo (Universitat Rovira i Virgili, Catalonia)
- Jerry Reiter (Duke University, USA)
- Yosef Rinott (Hebrew University, Israel)
- Steven Ruggles (University of Minnesota, USA)
- Nicolas Ruiz (OECD, European Union)
- Pierangela Samarati (University of Milan, Italy)
- David S·nchez (Universitat Rovira i Virgili, Catalonia)
- Eric Schulte-Nordholt (Statistics Netherlands)
- Natalie Shlomo (University of Manchester, UK)
- Aleksandra Slavkovic (Penn State University, USA)
- Jordi Soria-Comas (Catalan Data Protection Authority, Catalonia)
- Tamir Tassa (The Open University, Israel)
- Vicenc Torra (National University of Ireland-Maynooth, Ireland)
- Lars Vilhuber (Cornell University, USA)
PROGRAM CHAIR
- Josep Domingo-Ferrer (UNESCO Chair in Data Privacy, Universitat Rovira
i Virgili, Catalonia)
GENERAL CHAIR
- Krishnamurty Muralidhar (The University of Oklahoma, USA)
ORGANIZATION COMMITTEE
- Joaquin Garcia-Alfaro (Telecom SudParis, France)
- Giulia Lombardi (The University of Oklahoma, Italy)
- Jesus Manjon (Universitat Rovira i Virgili, Catalonia)
- Romina Russo (Universitat Rovira i Virgili, Catalonia)
3. TOPICS OF INTEREST
---------------------
Topics of interest include but are not limited to:
- New anonymization methods for tabular data
- New anonymization methods for microdata (including non-conventional
microdata types such as trajectories, graphs, etc.)
- Best anonymization practices for tabular data
- Best anonymization practices for microdata
- Co-utility for privacy preservation
- Big data anonymization
- Streaming data anonymization
- Decentralized anonymization
- Balancing data quality and data confidentiality in SDC
- Differential privacy and other privacy models
- SDC transparency issues
- Onsite access centers
- Remote access facilities
- SDC software
- Estimating disclosure risk in SDC
- Record linkage methods
- Real-life disclosure scenarios in EU-member states and abroad
- Privacy preserving data mining (both cryptographic and non-cryptographic)
- Private information retrieval
- Privacy in web-based e-commerce
- Privacy in healthcare
- Privacy in official and corporate statistics
- Other data anonymization issues
4. SUBMISSIONS
--------------
Full papers containing either original technical contributions or
high-quality surveys on the above topics or on related topics are
sought.
Camera-ready versions of accepted papers should be prepared using the
LaTeX2estyle or the Word template of Springer Verlag Lecture Notes in
ComputerScience. For LaTeX2e, a macro package llncs.zip and an example
file typeinst.zip can be downloaded from
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu….
For Microsoft Word, a template word.zip can be downloaded from the
same page above.
We encourage authors to use the above formats already for their
submissions.
LENGTH OF SUBMISSIONS.
Using the above format with 11 point font, the paper should be at most
12 pages excluding bibliography and appendices, and at most 16 pages
total. Committee members are not required to read appendices; the
paper should be intelligible without them. Submissions not meeting
these guidelines risk rejection without consideration of their merits.
5. PROCEEDINGS
--------------
Among PSD 2020 accepted papers, a selection will be made based on
quality and coverage and the selected papers will be published in the
Lecture Notes in Computer Science (LNCS) series by Springer. This
follows the tradition of the previous PSD conferences.
The remaining accepted papers will be published in a USB with an ISBN.
It is possible to submit a paper directly for the USB, which benefits
from a later submission deadline (see USB-only dates below).
The form of publication of an accepted paper will be clearly specified
in the acceptance message. Both the LNCS volume and the CD will be
*available at the conference*.
6. IMPORTANT DATES
------------------
Submission deadline: **MAY 24, 2020**
Acceptance notification: June 26, 2020
Proceedings version due: July 5, 2020
USB-only submission deadline: July 5, 2020
USB-only acceptance notification: July 15, 2020
USB-only proceedings version due: July 22, 2020
Conference: Sep. 23-25, 2020
7. VENUE AND TRAVEL
-------------------
The conference will take place at the San Francesco classroom annex of
the 'Oklahoma University in Arezzo' facilities, located in the city of
Arezzo.
OU in Arezzo. San Francesco Classroom annex
Piazza San Francesco, 18
Arezzo, Italy 52100
http://www.ou.edu/cis/education_abroad/programs/ou-in-arezzo
Further venue, travel and accommodation information will be posted in
due course at http://unescoprivacychair.urv.cat/psd2020
A number of travel grants are made available by the UNESCO Chair in
Data Privacy, especially for authors and delegates from transition
countries. Information on grants is posted in the conference web site.
8. REGISTRATION
---------------
Registration information will be posted no later than June 2020 at
http://unescoprivacychair.urv.cat/psd2020
Apologies if you receive multiple copies of this email!
============================================================
15th Workshop on Workflows in Support of Large-Scale Science
(WORKS20)
to be held in conjunction with
SC 2020, Sun Nov 15, 9am-5:30pm
Atlanta, GA, USA
https://works-workshop.org
============================================================
Scientific workflows have been almost universally used across scientific domains and have underpinned some of the most significant discoveries of the past several decades. Workflow management systems (WMSs) provide abstraction and automation which enable a broad range of researchers to easily define sophisticated computational processes and to then execute them efficiently on parallel and distributed computing systems. As workflows have been adopted by a number of scientific communities, they are becoming more complex and require more sophisticated workflow management capabilities. A workflow now can analyze terabyte-scale data sets, be composed of one million individual tasks, require coordination between heterogeneous tasks, manage tasks that execute for milliseconds to hours, and can process data streams, files, and data placed in object stores. The computations can be single core workloads, loosely coupled computations, or tightly all within a single workflow, and can run in dispersed computing platforms.
This workshop focuses on the many facets of scientific workflow management systems, ranging from actual execution to service management and the coordination and optimization of data, service, and job dependencies. The workshop covers a broad range of issues in the scientific workflow lifecycle that include: scientific workflows representation and enactment; workflow scheduling techniques to optimize the execution of the workflow on heterogeneous infrastructures; workflow enactment engines that need to deal with failures in the application and execution environment; and a number of computer science problems related to scientific workflows such as semantic technologies, compiler methods, scheduling and fault detection and tolerance.
WORKS20 will be held in conjunction with the SuperComputing (SC20), Atlanta, Georgia, USA, at Georgia World Congress Center (GWCC).
Topics
------
WORKS20 welcomes original submissions in a range of areas, including but not limited to:
* Big Data analytics workflows
* Data-driven workflow processing (including stream-based workflows)
* Workflow composition, tools, and languages
* Workflow execution in distributed environments (including HPC, clouds, and grids)
* Reproducible computational research using workflows
* Dynamic data dependent workflow systems solutions
* Exascale computing with workflows
* In Situ Data Analytics Workflows
* Interactive workflows (including workflow steering)
* Workflow fault-tolerance and recovery techniques
* Workflow user environments, including portals
* Workflow applications and their requirements
* Workflow optimizations (including scheduling and energy efficiency)
* Performance analysis of workflows
* Workflow debugging
* Workflow provenance
* Machine Learning workflows
Papers should present original research and should provide sufficient background material to make them accessible to the broader community.
Important Dates
---------------
Full paper deadline: August 15, 2020
Paper acceptance notification: September 15, 2020
E-copyright registration completed by authors: October 1, 2020
Camera-ready deadline: October 1, 2020
Workshop: November 15, 2020
---------------------------------
Submission Guidelines:
Full submission will be up to 8 pages long including references. All submitted papers will undergo a rigorous review process and each will have at least three reviews by members of the program committee. Papers will be accepted based on their technical contributions.
---------------------------------
Organizing Committee
- Rafael Ferreira da Silva, University of Southern California, USA
- Rosa Filgueira, University of Edinburgh, UK
General Chair
- Ian Taylor, Cardiff University, UK, University of Notre Dame, USA
Steering Committee
- David Abramson, University of Queensland, Australia
- Malcolm Atkinson, University of Edinburgh, UK
- Ewa Deelman, University of Southern California, USA
- Michela Taufer, University of Tennessee
Publicity Chair
- Hoang Anh Nguyen, University of Queensland, Australia
Program Committee (tentative)
- Pinar Alper – King's College London, UK
- Ilkay Altintas – SDSC, USA
- Khalid Belhajjame Universit. Paris-Dauphine, France
- Ivona Brandic – TU Wien, Austria
- Kris Bubendorfer – VUW, New Zealand
- Jesus Carretero – Universidad Carlos III de Madrid, Spain
- Henri Casanova – University of Hawaii at Manoa, USA
- Rafael Ferreira da Silva – USC/ISI, USA
- Daniel Garijo – USC/ISI, USA
- Sandra Gesing – University of Notre Dame, USA
- Tristan Glatard – Concordia University, Canada
- Daniel Katz – UIUC, USA
- Tamas Kiss – University of Westminster, UK
- Dagmar Krefting – HTW Berlin, Germany
- Maciej Malawski – AGH UST, Poland
- Anirban Mandal – RENCI, USA
- Marta Mattoso – UFRJ, Brazil
- Paolo Missier – Newcastle University, UK
- Hoang Anh Nguyen, University of Queensland, Australia
- Jarek Nabrzyski – University of Notre Dame, USA
- Daniel de Oliveira – UFF, Brazil
- Ilia Pietri, Intracom SA Telecom Solutions, Greece
- Loic Pottier – USC/ISI, USA
- Radu Prodan – University of Innsbruck, Austria
- Omer Rana – Cardiff University, UK
- Ivan Rodero – Rutgers University, USA
- Rizos Sakellariou – University of Manchester, UK
- Frédéric Suter – CNRS, France
- Andrew Stephen Mcgough – Newcastle University, UK
- Domenico Talia – University of Calabria, Italy
- Douglas Thain – University of Notre Dame, USA
- Rafael Tolosana-Calasanz – Universidad de Zaragoza, Spain
- Chase Wu – NJ Institute of Technology, USA
Dear Computer Vision/Machine Learning/Autonomous Systems students,
engineers, scientists and enthusiasts,
Artificial Intelligence and Information analysis (AIIA) Lab, Aristotle
University of Thessaloniki, Greece is proud to launch the live CVML Web
lecture series that will cover very important topics Computer vision/machine
learning. Two lectures will take place on Saturday 25th April 2020:
1) Introduction to Autonomous Systems
2) Introduction to Computer Vision
Date/time:
a) Saturday 11:00-12:30 EET (17:00-18:30 Beijing time) for audience in Asia
and
b) Saturday 20:00-21:30 EET (13:00-14:30 EST, 10:00-11:30 PST for NY/LA,
respectively) for audience in the Americas.
Registration can be done using the link:
<http://icarus.csd.auth.gr/cvml-web-lecture-series/>
http://icarus.csd.auth.gr/cvml-web-lecture-series/
Lectures abstract
1) Introduction to Autonomous Systems
Abstract: Mission planning and control, perception and intelligence,
embedded computing, swarm systems, communications and societal technologies.
a) autonomous cars, b) drones and drone swarms, c) autonomous underwater
vehicles d) autonomous marine vessels and e) autonomous robots.
2) Introduction to Computer Vision
Abstract: image/video sampling, Image and video acquisition, Camera
geometry, Stereo and Multiview imaging, Structure from motion, Structure
from X, 3D Robot Localization and Mapping, Semantic 3D world mapping, 3D
object localization, Multiview object detection and tracking, Object pose
estimation.
Lecturer: Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer,
EURASIP fellow) received the Diploma and PhD degree in Electrical
Engineering, both from the Aristotle University of Thessaloniki, Greece.
Since 1994, he has been a Professor at the Department of Informatics of the
same University. He served as a Visiting Professor at several Universities.
His current interests are in the areas of image/video processing, machine
learning, computer vision, intelligent digital media, human centered
interfaces, affective computing, 3D imaging and biomedical imaging. He has
published over 1138 papers, contributed in 50 books in his areas of interest
and edited or (co-)authored another 11 books. He has also been member of the
program committee of many scientific conferences and workshops. In the past
he served as Associate Editor or co-Editor of 9 international journals and
General or Technical Chair of 4 international conferences. He participated
in 70 R&D projects, primarily funded by the European Union and is/was
principal investigator/researcher in 42 such projects. He has 30000+
citations to his work and h-index 81+ (Google Scholar).
Prof. Pitas lead the big European H2020 R&D project MULTIDRONE:
<https://multidrone.eu/> https://multidrone.eu/ and is principal
investigator (AUTH) in H2020 projects Aerial Core and AI4Media. He is chair
of the Autonomous Systems initiative
<https://ieeeasi.signalprocessingsociety.org/>
https://ieeeasi.signalprocessingsociety.org/.
Prof. I. Pitas:
<https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el>
https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el
AIIA Lab <http://www.aiia.csd.auth.gr> www.aiia.csd.auth.gr
Lectures will consist primarily of live lecture streaming and PPT slides.
Attendees (registrants) need no special computer equipment for attending the
lecture. They will receive the lecture PDF before each lecture and will have
the ability to ask questions real-time. Audience should have basic
University-level undergraduate knowledge of any science or engineering
department (calculus, probabilities, programming, that are typical e.g., in
any ECE, CS, EE undergraduate program). More advanced knowledge (signals and
systems, optimization theory, machine learning) is very helpful but nor
required.
These two lectures are part of a 14 lecture CVML web course 'Computer vision
and machine learning for autonomous systems' (April-June 2020):
1. Introduction to autonomous systems
2. Introduction to computer vision
3. Image acquisition, camera geometry
4. Stereo and Multiview imaging
5. 3D object/building/monument reconstruction and modeling
6. Signals and systems. 2D convolution/correlation
7. Motion estimation
8. Introduction to Machine Learning
9. Introduction to neural networks, Perceptron, backpropagation
10. Deep neural networks, Convolutional NNs
11. Deep learning for object/target detection
12. Object tracking
13. Localization and mapping
14. Fast convolution algorithms. CVML programming tools.
Sincerely yours
Prof. Ioannis Pitas, Director of AIIA Lab, Aristotle University of
Thessaloniki, Greece
[Apologies if you receive multiple copies of this CFP]
CALL FOR PAPERS
==========================================================
2020 BenchCouncil International Symposium on Benchmarking, Measuring and Optimizing
(Bench'20)
http://www.benchcouncil.org/bench20/index.html
Nov. 14th - Nov. 16th, 2020, Atlanta, Georgia, USA
==========================================================
Introduction
----------------
Benchmarking, measuring, and optimizing are fundamental human activities. The organizing committee is pleased to invite you to take part in Bench'20 to be held in Atlanta, Georgia, USA. This symposium (Bench'20) is organized by the International Open Benchmarking Council (BenchCouncil). Bench'20 overlaps with SC 20 (Same place and same time), but it is NOT affiliated with the SC conference. The main themes of Bench'20 are benchmarking, measuring, and optimizing Big Data, AI, Block Chain, HPC, Datacenter, IoT, Edge and other things.
The Bench conference has three defining characteristics. First, it provides a highquality, single-track forum for presenting results and discussing ideas that further the knowledge and understanding of the benchmark community as a whole. Second, it is a multi-disciplinary conference. The past conferences attracted the researchers and practitioners from the architecture, system, algorithms and application communities. Third, it includes both invited sessions and contributed sessions.
Regularly, Bench'20 will present the BenchCouncil Achievement Award (3000$), the BenchCouncil Rising Star Award (1000$), and the BenchCouncil Best Paper Award (1000$).
As its duty, BenchCouncil incubates, hosts benchmark projects, and further encourages reliable and reproducible research using the benchmarks from BenchCouncil or other organizations. To that end, we present the BenchCouncil Award for Excellence for Reproducible Research to the papers using all publicly available benchmarks. Each paper $100 prize, maximally up to 12 papers: 4 papers for each category of poster, spotlight, and oral.
Call for papers
------------------------
Specific topics of interest include, but are not limited to, the following.
**Synthetics or Real-world Data Sets of:
**Benchmark, measurement, and optimization of:
**Benchmark specifications and open-source implementation reports of:
** Methodologies, abstractions, metrics, algorithms, and tools in benchmark, measurement, and optimization for:
** Benchmark-driven domain-specific co-design of:
** Test methodologies and systems of:
** Workload characterization of:
-Big Data
-AI
-HPC
-Machine learning in HPC
-Big scientific data
-Datacenter
-Cloud
-Warehouse-scale computing
-Mobile robotics
-Edge and fog computing
-IoT
-Block chain
-Data management and storage
-Medicine, Finance and Education
Paper Submission
------------------------
Papers must be submitted in PDF. For a full paper, the page limit is 8 pages in standard two-column IEEE conference format or 12 pages in LNCS format, not including references. For a short paper, the page limit is 4 pages in standard twocolumn IEEE conference format or 6 pages in LNCS format, not including references. The submissions will be judged based on the merit of the ideas rather than the length. After the conference, the proceeding will be published by Springer LNCS (Indexed by EI). Please note that LNCS format is the final one for publishing.
After the acceptance decisions are made, the presentation mode of each paper is determined based on the recommendations as poster, spotlight, or oral. All accepted papers, regardless of presentation mode, appear in the proceedings as full-length papers.
At least one author must pre-register for the symposium, and at least one author must attend the symposium to present the paper. Papers for which no author is preregistered will be pulled from the proceedings.
Submission site:
https://easychair.org/my/conference?conf=bench20#
Improtant Dates
---------------------
Registration of abstract (non-mandatory) June 15, 2020
Paper Submission July 15, 2020
Acceptance Notification Aug 15, 2020
Awards
----------
At Bench'20, several important awards will be given, which include:
* BenchCouncil Achievement Award ($3,000)
- This award recognizes a senior member who has made long-term contributions to benchmarking, measuring, and optimizing. The winner is eligible for BenchCouncil Fellow.
* BenchCouncil Rising Star Award ($1,000)
- This award recognizes a junior member who demonstrates outstanding potential for research and practice in benchmarking, measuring, and optimizing.
* BenchCouncil Best Paper Award ($1,000)
- This award recognizes a paper presented at the Bench conferences, which demonstrates potential impact on research and practice in benchmarking, measuring, and optimizing.
* BenchCouncil Award for Excellence for Reproduceable Research (Each paper $100 prize, maximally up to 12 papers: 4 papers for each category of poster, spotlight, and oral)
- BenchCouncil incubates, hosts benchmark projects, and further encourages reliable and reproducible research using the benchmarks from BenchCouncil or other organizations. To that end, we present the BenchCouncil Award for Excellence for Reproducible Research to the papers using all publicly available benchmarks.
Organization
-----------------
General Chairs
Jianfeng Zhan (BenchCouncil and Chinese Academy of Sciences)
TPC Chairs
Wanling Gao (ICT, Chinese Academy of Sciences)
Award Committees
Lizy Kurian John (The University of Texas at Austin)
D. K. Panda (The Ohio State University)
Geoffrey Fox (Indiana University)
Jianfeng Zhan (BenchCouncil and Chinese Academy of Sciences)
Submission Chair
Rui Ren (Cyberspace Security Research Institute Co., Ltd.)
Publicity Chairs
Chen Zheng (Institute of Computing Technology, CAS)
Zhen Jia (Amazon)
Biwei Xie (ICT, Chinese Academy of Sciences)
Technical Program Committee
----------------------------------------
Woongki Baek, UNIST
Piotr Luszczek, University of Tennessee Knoxville
Khaled Ibrahim, Lawrence Berkeley National Lab
Lei Wang, ICT, Chinese Academy of Sciences
Vladimir Getov, University of Westminster
Gwangsun Kim, POSTECH
Hyogi Sim, Oak Ridge National Laboratory
Zhen Jia, Amazon
Bin Ren, Pacific Northwest National Laboratory
Nikhil Jain, Lawrence Livermore National Laboratory
Lucas Mello Schnorr, UFRGS
Bo Wu, Colorado School of Mines
Jungang Xu, College of Computer and Control Engineering,University of Chinese Academy of Sciences
Ryan E. Grant, Sandia National Laboratories
Huan Liu, Arizona State University
Chen Zheng, ICT, Chinese Academy of Sciences
Zhihui Du, Tsinghua University
Salman Zubair Toor, Uppsala University
Arne Berre, SINTEF
Todor Ivanov, Frankfurt Big Data Lab, Goethe University Frankfurt
Biwei Xie, ICT, Chinese Academy of Sciences
Benson Muite, University of Tartu
K. Selcuk Candan, Arizona State University
Feiyi Wang, Oak Ridge National Laboratory
Xiaoyi Lu, The Ohio State University
Ben Blamey, Uppsala University
Rui Ren, Cyberspace Security Research Institute Co., Ltd.
Juby Jose, Intel