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CFP - 37th International Conference on Logic Programming (extended deadlines)
by Miguel Areias 04 May '21

04 May '21

========================================================================= FINAL CALL FOR PAPERS The 37th International Conference on Logic Programming (ICLP 2021) Fully virtual event hosted by the Department of Computer Science of the University of Porto ========================================================================= New: Extended deadlines (regular papers) ** Abstract registration: May 12, 2021 ** Paper submission: May 18, 2021 New: Invited speakers ** William W. Cohen, Google AI ** John Hooker, CMU ** Phokion Kolaitis, UC Santa Cruz and IBM Almaden ** Stuart Russell, UC Berkeley ** Jeffrey Ullman, Stanford University ========================================================================= Contributions are sought in all areas of logic programming, including but not restricted to: ** Foundations: Semantics, Formalisms, Nonmonotonic reasoning, Knowledge representation. ** Languages issues: Concurrency, Objects, Coordination, Mobility, Higher order, Types, Modes, Assertions, Modules, Meta-programming, Logic-based domain-specific languages, Programming techniques. ** Programming support: Program analysis, Transformation, Validation, Verification, Debugging, Profiling, Testing, Execution visualization. ** Implementation: Compilation, Virtual machines, Memory management, Parallel/distributed execution, Constraint handling rules, Tabling, Foreign interfaces, User interfaces. ** Related Paradigms and Synergies: Inductive and coinductive logic programming, Constraint logic programming, Answer set programming, Interaction with SAT, SMT and CSP solvers, Theorem proving, Argumentation, Probabilistic programming, Machine learning. ** Applications: Databases, Big data, Data integration and federation, Software engineering, Natural language processing, Web and semantic web, Agents, Artificial intelligence, Computational life sciences, Cybersecurity, Robotics, Education. Tracks and Affiliated Events **************************** Besides the main track, ICLP 2021 will host additional tracks: ** Applications Track ** Recently Published Research Track and affiliated events: ** MentorLP - Mentoring Workshop on Logic Programming ** Fall School on Logic and Constraint Programming ** Doctoral Consortium ** Tutorials and co-located Workshops More details ************ https://iclp2021.dcc.fc.up.pt Any additional question can be directed towards ICLP Chairs: iclp2021(a)easychair.org =========================================================================

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PhD Position at CIAD / Technology University of Belfort-Montbaliard on "Contribution to cooperative perception and cooperative planning and control of robots in uncertain environment"
by Stéphane Galland 03 May '21

03 May '21

The CIAD laboratory is searching for a PhD candidate to work on cooperative control and planning, cooperative environmental perception,machine learning, multi-agent systems and robot behavior analysis. The PhD project is funded by the Technology University of Belfort- Montbeliard for 36 months.Starting period is September/October 2021. Application details are into the attached file or available on https://www.linkedin.com/feed/update/urn:li:activity:6794917064424341505/ 1) Introduction / background: Several applications in the field of robotics require interactions between robots toaccomplish their task. These interactions can be conflictual as in the case of space sharing,or collaborative as during handling operations. The movements of the robots in both casesmust be synchronized to perform their tasks safely. Due to the uncertain environment,especially in the presence of humans, these movements can experience delays, hence theneed to share the perception of the environment. There are two possible solutions tomeet this need. The first one consists of building a global dynamic representation mapshared and updated by all robots. This assumes that it must be managed centrally. In thesecond approach, which is decentralized, the robots communicate interfering elementswith each other. To do this, they must be able to classify the states of the environmentand jointly define the different sources of delay to synchronize accordingly. Two scientificbuilding blocks are identified in the proposed thesis subject.Cooperative planning and control: This involves studying interaction models and analyzing theproperties of control or trajectory planning. In addition to the properties of the solutions, themodel will be used to deduce the relevant information to be exchanged between the robots.Other control or planning techniques can be exploited. Through these analyzes, the student will beable to address the thorny issue of multi-agent reinforcement learning in the context ofcontinuous decision-making [1]. The aim here is to test the potentials of Deep ReinforcementLearning (DRL) in the context of the learning of several agents [2]. Also, other distributed controlstrategies can be deduced, explored and compared.Dynamic cooperative perception: This involves sharing the perception of a robot's environmentwith other robots and vice versa in a collaborative context [3]. The objective is to increase theperception of each of the robots in order to offer them broader perspectives to carry out theirindividual and collective tasks as well as possible [4]. In general, each robot, equipped with one ormore sensors (cameras, Lidars, etc.), must be able to locally perceive its surrounding space, thenintegrate all the information useful for the mission of each robot in its perception or knowledgemap [5]. The student will focus particularly on creating a dynamic representation of the perceptionof each robot by exploiting its own perception and those shared by other robots. The objectivehere is to understand the dynamic content of the environment by recognizing situations or eventsthat may cause difficulties to the robot itself, but also to other robots participating in the collectivemission. This representation requires a spatial and temporal registration, which can be complexdepending on the type of information shared.2) Planned works:The two scientific topics presented above will have to be treated and exploited jointly.Cooperative control and planning can benefit fromdynamic cooperative perception and vice versa.Indeed, the results of perception will be exploited to optimize the control of the robots, and inreturn, the perception process will exploit the robots control or planning to improve theirperception in terms of prediction for example. From a practical point of view, the sharing andupdating of the perception map of each robot can be done at the request of the robot concerned(to other robots) or can be detected automatically as part of a strategy defined by the missionitself and made known to all robots participating in the mission.For experiment and testing, the student will benefit from an application in a concrete case ofcollaboration between several real robots and a computing platform. The data will be generatedthrough real and augmented tests. [1] Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, and Igor Mordatch. 2017. Multi-agentactor-critic for mixed cooperative-competitive environments. In Proceedings of the 31stInternational Conference on Neural Information Processing Systems (NIPS'17). Curran AssociatesInc., Red Hook, NY, USA, 6382–6393.[2] OROOJLOOYJADID, Afshin et HAJINEZHAD, Davood. A review of cooperative multi-agent deepreinforcement learning. arXiv preprint arXiv:1908.03963, 2019.[3] SCHMUCK, Patrik et CHLI, Margarita. CCM ‐ SLAM: Robust and efficient centralized collaborativemonocular simultaneous localization and mapping for robotic teams. Journal of Field Robotics,2019, vol. 36, no 4, p. 763-781.[4] QUERALTA, Jorge Pena, TAIPALMAA, Jussi, PULLINEN, Bilge Can, et al. Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision. IEEE Access,2020, vol. 8, p. 191617-191643.[5] YANG, Chule, WANG, Danwei, ZENG, Yijie, et al. Knowledge-based multimodal informationfusion for role recognition and situation assessment by using mobile robot. Information Fusion,2019, vol. 50, p. 126-138.-- Laboratoire Connaissance et Intelligence Artificielle Distribuées CIAD UMR 7533 Prof. Dr. Stéphane GALLAND Full Professor of Computer Science and Multiagent Systems Deputy Director of CIAD French Head of ARFITEC ARF-17-11 & ARF-19-11 "Energy, Transport, Industry, Challenges for tomorrow" Senior member of the Multiagent Group Member of AFIA Université de Technologie de Belfort-Montbéliard - UBFC 13, rue Ernest Thierry-Mieg 90010 Belfort Cedex, FRANCE CIAD Lab: www.ciad-lab.fr Web: www.ciad-lab.fr/author-10836 Phone: +33 384 583 418 (work office)

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Ada-Europe Int.Conf. Reliable Software Technologies, AEiC 2021
by Dirk.Craeynest＠cs.kuleuven.be 27 Apr '21

27 Apr '21

----------------------------------------------------------------------- Call for Participation *** PROGRAM SUMMARY *** 25th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2021) 7-10 June 2021, Virtual Event www.ada-europe.org/conference2021 Organized by University of Cantabria and Ada-Europe in cooperation with ACM SIGAda, SIGPLAN, SIGBED and the Ada Resource Association (ARA) #AEiC2021 #AdaEurope #AdaProgramming ----------------------------------------------------------------------- *** General Information The 25th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2021), initially scheduled to take place in Santander, Spain, will be held online from the 7th to the 10th of June 2021, using the underline.io conference platform. The conference program includes parallel tutorials on Monday 7th, and a technical program and vendor exhibition from Tuesday to Thursday. The conference also includes breaks and virtual social events that will allow networking among the participants. *** Overview of the Week Monday 7th - Welcome Social Event - 5 Parallel Tutorials - Ice-Breaking Social Event Tuesday 8th - Ice-Breaking Social Event and Opening - Techn. Session 1: Scheduling and mixed-criticality systems - Keynote 1 - Techn. Session 2: Software modeling - Social Event Wednesday 9th - Welcome Social Event - Techn. Session 3: Autonomous systems - Work-in-Progress Session - Keynote 2 - Techn. Session 4: Ada issues and Ravenscar - Social Event Thursday 10th - Welcome Social Event - Techn. Session 5: Validation and verification tools - Techn. Session 6: Emerging applications with reliability requirements - Keynote 3 - Techn. Session 7: Safety challenges - Best Presentation Award, Closing Session and Party The program runs between 12:30 and 18:30 CEST, to allow participation from different time zones. For full details and up-to-date information, see the conference web page: http://www.ada-europe.org/conference2021 *** Keynote Talks In each of the three main conference days, a keynote will be delivered to address hot topics of relevance in the conference scope, with ample time for questions and answers. The keynotes will be: - Ángel Conde, Data Analytics and Artificial Intelligence team leader at IKERLAN (Spain), who will present his work on "Software reliability in the Big Data era with an industry-minded focus". - Alfons Crespo, who is with the Institute of Automation and Industrial Informatics of the Universitat Politècnica de València (Spain), will give an answer to the question "Why hypervisor-based approach is the best alternative for mixed-criticality systems". - Tucker Taft, who is Director of Language Research at AdaCore (USA), will talk on "A sampling of Ada 2022". *** Technical Sessions Given the current sanitary situation and the need to resort to a virtual format for the conference, we will all experience the advantages and benefits of exploring new formats. The technical sessions are designed with the flipped-conference concept, where the audience can access the pre-recorded presentation materials in advance and the live sessions are devoted to short presentations of the highlights of each contribution, allowing ample time for questions and answers with the presenter. The recorded materials will also be available for some time after their sessions. The technical sessions include papers submitted to the journal track that are heading towards final acceptance and open-access publication, together with industrial, invited and vendor presentations. *** Work-in-Progress Session The Work-in-Progress session contains contributions of evolving and early-stage ideas, or new research directions. They are presented in a special session consisting of a round of very short presentations of the highlights of each contribution, followed by a poster session in the same virtual space where the breaks are held. *** Exhibition From Tuesday to Thursday the conference platform will provide access to virtual booths where participants will be able to find information on the conference exhibitors and chat with them or request meetings. The virtual break lounge where the breaks and social events will take place will also have a space for meeting with the exhibitors. *** Tutorials Five four-hour parallel tutorials are offered on Monday 7th: - TU-1: Programming mobile robots with ROS2 and the RCLAda Ada client library, by Alejandro R. Mosteo - TU-2: Introduction to the development of safety critical software, by Jean-Pierre Rosen - TU-3: Parallel programming with Ada and OpenMP, by Sara Royuela, S. Tucker Taft, Luis Miguel Pinho - TU-4: Timing verification from UML & MARTE design models: techniques & tools, by Laurent Rioux, Julio Medina and Shuai Li - TU-5: Programming shared memory computers, by Jan Verschelde *** Social Program The virtual conference platform will offer a space under the gather.town environment to allow informal and lively gathering of the participants. This space may have different areas, such as rooms, tables, and corners where a participant can approach to talk though videoconferencing with participants in the same virtual area. This facility will be used for the breaks, poster session, exhibition and social events. Particular themes for some of the social events will be announced in the conference platform and in the web page. *** Further Information Participation for the full event, including tutorials, is free for Ada-Europe members and only 60 EUR for all others. Registration is required for all. The conference web page will shortly give full and up-to-date details on the program, the registration process and the virtual platform: http://www.ada-europe.org/conference2021 *** AEiC 2021 Sponsors - AdaCore: https://www.adacore.com/ - Ellidiss: https://www.ellidiss.com/ - PTC: http://www.ptc.com/developer-tools - Universidad de Cantabria: https://web.unican.es/en/ - Vector: https://www.vector.com/at/en/ The conference is supported and sponsored by - Ada-Europe: http://www.ada-europe.org/ and organized in cooperation with - ACM SIGAda: http://www.sigada.org/ - ACM SIGBED: https://sigbed.org/ - ACM SIGPLAN: http://www.sigplan.org/ - ARA: https://www.adaic.org/community/ ----------------------------------------------------------------------- Our apologies if you receive multiple copies of this announcement. Please circulate widely. Dirk Craeynest, AEiC 2021 Publicity Chair (aka Ada-Europe 2021) Dirk.Craeynest(a)cs.kuleuven.be

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CAS at ICCSA 2021: New Conference Dates and Deadlines
by Ana Cristina Silva Braga 27 Apr '21

27 Apr '21

Dear Colleague, ICCSA 2021 will be organized as a virtual conference with online-only participation (which includes online attendance and presentation in sessions, and the publication of papers in Springer LNCS or IEEE CPS conference proceedings) Optional in-presence participation may be organized, should the COVID-19 restrictions allow it. The Organizing Committee decided to move the dates of the conference to 13-16 September 2021 to benefit from the vaccine effect and to have a higher number of participants in person. Registration fees: * Virtual conference online-only participation: 150 Euro * Optional in-presence participation: regular 520 Euro, students 340 Euro, workshop chair 315 Euro ***************************************************************************** ********************** APOLOGIES FOR MULTIPLE COPIES RECEIVED ****************** ************************** CAS 2021 at ICCSA 2021 ******************************* ************************University of Cagliari, Cagliari, Italy ************************ *************************** NEW CONFERENCE DATES **************************** ***************************************************************************** Computational and Applied Statistics (CAS 202<https://cas2020.webnode.com/>1) Workshop of the 21th International Conference on Computational Science and Applications (ICCSA 2021, http://www.iccsa.org/) will be held in Cagliari, Italy. TOPICS ====== The aim of CAS workshop is to bring together scientists working in computational statistics, scientific computation and applications in all areas of sciences, engineering, industry, economics, life sciences and social sciences. Topics of interest include (but are not limited to): * Computational Statistics: new issues in the design of computational algorithms for implementing statistical methods, development in R, etc * Applications: statistical case study in all areas of sciences, engineering and industry, including economics, medicine, biology, earth sciences and social sciences. IMPORTANT DATES (NEW) ====================== May 10, 2021: Deadline for paper submission to the General Tracks (Workshops may select a different deadline) June 6, 2021: Notification of Acceptance. June 21, 2021: Submission deadline for the final version of the Proceeding Papers (firm deadline). June 28, 2021: Registration ends (firm deadline). September 13-16, 2021: ICCSA 2021 Conference PROCEEDINGS ============ The proceedings of the CAS 2021 Workshop will appear in the Springer-Verlag, Lecture Notes in Computer Science (LNCS) series. The paper must be camera-ready, between 10 and 16 pages long and formatted according to the LNCS rules SUBMISSION DETAILS ================== All accepted papers will be included in the Springer Lecture Notes in Computer Science (LNCS, http://www.springer.com/gp/computer-science/lncs ) series and indexed by Scopus, EI Engineering Index, Thomson Reuters Conference Proceedings Citation Index (included in ISI Web of Science), and several other indexing services. The papers will contain linked references, XML versions and citable DOI numbers. Submitted papers will be subject to stringent peer review by at least three experts and carefully evaluated based on originality, significance, technical soundness, and clarity of exposition. The authors can submit abstracts and papers to your session accessing the electronic submission site: http://ess.iccsa.org/ You can find the instructions to prepare and submit papers on the web site: http://www.iccsa.org/instructions-for-authors If you are not registered, you must to register before the submission. From the personal page the author is able to submit first an abstract (phase 1), then a full paper (phase 2), selecting the session from the list of sessions in the submission forms. The author will be able to update the paper until the submission deadline. ORGANIZER =========== * Ana Cristina Braga (acb(a)dps.uminho.pt<mailto:acb@dps.uminho.pt>), Dep. of Production and Systems (University of Minho), Algoritmi Research Centre (University of Minho), Portugal. If you have some doubts or problems, do not hesitate to contact the organizer. Best regards, Ana Cristina Braga (CAS 2021 organizer)

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Distinguished Lecture by Prof. Milind Tambe: ‘AI for Social Impact: Results from deployments for public health and conservation’
by COMP HKBU 27 Apr '21

27 Apr '21

Dear Sir or Madam, You are cordially invited to attend the *HKBU Faculty of Science 60th Anniversary Distinguished Lecture by Prof. Milind Tambe*, which will be held on* Thursday, 13 May 2021 HKT (GMT+8) *via *Zoom Webinar*. Please register at http://bit.ly/d-reg on or before 12:00nn, 12 May 2021 (HKT). Details are as follows:- *Abstract* With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. I focus on the problems of public health and conservation, and address one key cross-cutting challenge: how to effectively deploy our limited intervention resources in these problem domains. I will present results from work around the globe in using AI for HIV prevention, Maternal and Child care interventions, TB prevention and COVID modeling, as well as for wildlife conservation. Achieving social impact in these domains often requires methodological advances. To that end, I will highlight key research advances in multiagent reasoning and learning, in particular in, computational game theory, restless bandits and influence maximization in social networks. In pushing this research agenda, our ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques. *Biography* Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research in Computation and Society at Harvard University; concurrently, he is also Director "AI for Social Good" at Google Research India. He is a recipient of the IJCAI John McCarthy Award, ACM/SIGAI Autonomous Agents Research Award from AAMAS, AAAI Robert S Engelmore Memorial Lecture award, INFORMS Wagner prize, Rist Prize of the Military Operations Research Society, Columbus Fellowship Foundation Homeland security award, over 25 best papers or honorable mentions at conferences such as AAMAS, AAAI, IJCAI and meritorious commendations from agencies such as the US Coast Guard and the Los Angeles Airport. Prof. Tambe is a fellow of AAAI and ACM. For more details, please visit https://www.comp.hkbu.edu.hk/dlecture/ . If you have any questions, please feel free to contact comp(a)comp.hkbu.edu.hk . Thank you. Best regards, Department of Computer Science Hong Kong Baptist University

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Last call: Invitation to join 2021 Spring School 'CVML Short Course - Computer Vision for Autonomous Systems', 5-6th May 2021 (6th edition)
by Ioanna Koroni 27 Apr '21

27 Apr '21

Dear Computer Vision, Deep Learning and/or Autonomous systems engineers, scientists and enthusiasts, you are welcomed to register in this CVML Short e-course on 'Computer Vision for Autonomous Systems', 5-6th May 2021: <https://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-aut onomous-systems/> https://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-auto nomous-systems/ It will take place as a two-day e-course (due to COVID-19 circumstances), hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures delivered through a tele-education platform. They will be complemented with on-line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues and to enable you to study at own pace. You can also self-assess your knowledge, by filling appropriate questionnaires (one per lecture). You will be provided programming exercises to improve your programming skills. It is part of the very successful CVML short course series that took place in the last three years. The short e-course consists of 16 1-hour live lectures organized in two Parts (1 Part per day): Part A lectures (8 hours) provide an in-depth presentation of 2D and 3D Computer Vision theory and applications in the above-mentioned diverse domains, primarily for semantic 3D world modeling and localization. Computer Vision starts with a detailed presentation of digital image/video fundamentals and image acquisition and camera geometry, including camera calibration. Then, two lectures on: a) Stereo and Multiview imaging and b) Structure from motion will provide the theoretical and algorithmic tools to recover 3D world models from images. They will be used on Localization and mapping that is of primary importance in Autonomous Systems and Robotic perception. This is complemented by Neural techniques for recovering depth information and 3D world modeling, even from monocular images. Deep semantic image segmentation will conclude this part, by providing DNN methods both to label and segment regions, e.g., roads and targets, e.g., cars, pedestrians. Part B lectures (8 hours) will start with an overview of Autonomous Systems Sensors. Then , it will provide an in-depth presentation of Computer Vision theory and applications in autonomous systems, particularly as related to target detection, tracking and object pose estimation. Applications will be presented for Multiple Drone Systems Autonomous Car Vision and Autonomous Marine Surface Vessels. Finally, CVML programming tools (e.g., DNN frameworks, BLAS/cuBLAS, DNN and CV libraries) are overviewed, as they allow fast application of all the above knowledge in almost any application domain. Course lectures Part A: Computer Vision (first day, 8 lectures) 1. Digital images and videos 2. Image Acquisition. Camera Geometry 3. Stereo and Multiview Imaging 4. Structure from Motion 5. 3D Robot Localization and Mapping 6. Neural 3D world modeling 7. Image/Point cloud registration 8. Deep semantic image segmentation Part B: Autonomous Systems (second day, 8 lectures) 1. Autonomous Systems Sensors 2. Deep object detection 3. Object Tracking 4. Object Pose Estimation 5. Multiple Drone Systems 6. Autonomous Car Vision 7. Autonomous Surface Vessels 8. CVML Software Development Tools Though independent, the attendees of this short e-course will greatly benefit by attending the CVML Short e-course on 'Machine Learning and Deep Neural Networks' 27-28th April 2021: <http://icarus.csd.auth.gr/spring-cvml-short-course-machine-learning-and-dee p-neural-networks/> http://icarus.csd.auth.gr/spring-cvml-short-course-machine-learning-and-deep -neural-networks/ You can use the following link for course registration: <http://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-auto nomous-systems/> http://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-auton omous-systems/ Lecture topics, sample lecture ppts and videos, self-assessment questionnaires and programming exercises can be found therein. For questions, please contact: Ioanna Koroni < <mailto:koroniioanna@csd.auth.gr> koroniioanna(a)csd.auth.gr> The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow, Chair of the IEEE SPS Autonomous Systems Initiative, Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece, Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He is head of the EC funded AI doctoral school of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in Europe). He has 32200+ citations to his work and h-index 85+. AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking. Relevant links: 1) Prof. I. Pitas: <https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el> https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el 2) Horizon2020 EU funded R&D project Aerial-Core: <https://aerial-core.eu/> https://aerial-core.eu/ 3) Horizon2020 EU funded R&D project Multidrone: <https://multidrone.eu/> https://multidrone.eu/ 4) Horizon2020 EU funded R&D project AI4Media: <https://ai4media.eu/> https://ai4media.eu/ 5) AIIA Lab: <https://aiia.csd.auth.gr/> https://aiia.csd.auth.gr/ Sincerely yours Prof. I. Pitas Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab) Aristotle University of Thessaloniki, Greece Post scriptum: To stay current on CVML matters, you may want to register in the CVML email list, following instructions in: <https://lists.auth.gr/sympa/info/cvml> https://lists.auth.gr/sympa/info/cvml -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus

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Call for Papers: The 7th Int. Conf. on Machine Learning, Optimization & Data Science – LOD 2021, October 5-8, 2021 – Grasmere, Lake District, England – UK - Paper Submission Deadline: April 29
by Ludovico Montalcini 26 Apr '21

26 Apr '21

Dear Colleague, Apologies if you receive multiple copies of this announcement. Please kindly help forward it to potentially interested authors/attendees, thanks! -- The 7th International Conference on Machine Learning, Optimization, and Data Science – LOD 2021 - October 5-8, 2021 – Grasmere, Lake District, England – UK LOD 2021, An Interdisciplinary Conference: Machine Learning, Optimization, Big Data & Artificial Intelligence without Borders https://lod2021.icas.cc lod(a)icas.cc PAPERS SUBMISSION: All papers must be submitted using EasyChair: https://easychair.org/conferences/?conf=lod2021 Paper Submission deadline: Thursday April 29, 2021 (Anywhere on Earth) Any questions regarding the submission process can be sent to conference organizers: lod(a)icas.cc PAPER FORMAT: Please prepare your paper in English using the Springer Nature – Lecture Notes in Computer Science (LNCS) template, which is available here. Papers must be submitted in PDF. TYPES OF SUBMISSIONS: When submitting a paper to LOD 2021, authors are required to select one of the following four types of papers: * long paper: original novel and unpublished work (max. 15 pages in Springer LNCS format); * short paper: an extended abstract of novel work (max. 5 pages); * work for oral presentation only (no page restriction; any format). For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the conference; * abstract for poster presentation only (max 2 pages; any format). The poster format for the presentation is A0 (118.9 cm high and 84.1 cm wide, respectively 46.8 x 33.1 inch). For research work which is relevant and which may solicit fruitful discussion at the conference. Each paper submitted will be rigorously evaluated. The evaluation will ensure the high interest and expertise of reviewers. Following the tradition of LOD, we expect high-quality papers in terms of their scientific contribution, rigor, correctness, novelty, clarity, quality of presentation and reproducibility of experiments. Accepted papers must contain significant novel results. Results can be either theoretical or empirical. Results will be judged on the degree to which they have been objectively established and/or their potential for scientific and technological impact. It is also possible to present the talk virtually (Zoom). KEYNOTE SPEAKERS: * Ioannis Antonoglou, DeepMind, UK Topics: AlphaGO, Model-Based Reinforcement Learning Title: TBA * Paige Bailey, Microsoft, USA Topics: TensorFlow 2.0, Data Analysis, Machine Learning Title: Machine Learning with TF 2.x and JAX * Panos Pardalos, University of Florida, USA Topics: Optimization, Complex Networks & Data Science Title: TBA * Verena Rieser, Heriot Watt University, UK Topics: Natural Language Processing, Conversational AI, Spoken Dialogue Systems, Dialog, Natural Language Generation Title: Advances and Challenges in Conversational AI More Keynote Speakers Coming soon! TUTORIAL SPEAKER(S): * "Introduction to PyTorch" (4 hours), Thomas Viehmann, MathInf GmbH, Germany More Tutorial Speakers Coming soon! PAST LOD KEYNOTE SPEAKERS: https://lod2021.icas.cc/past-keynote-speakers/ Pierre Baldi, University of California Irvine, USA Yoshua Bengio, Head of the Montreal Institute for Learning Algorithms (MILA) & University of Montreal, Canada Bettina Berendt, TU Berlin, Germany & KU Leuven, Belgium, and Weizenbaum Institute for the Networked Society, Germany Jörg Bornschein, DeepMind, London, UK Michael Bronstein, Imperial College London, UK Nello Cristianini, University of Bristol, UK Peter Flach, University of Bristol, UK, and EiC of the Machine Learning Journal Marco Gori, University of Siena, Italy Arthur Gretton, UCL, UK Arthur Guez, Google DeepMind, Montreal, UK Yi-Ke Guo, Imperial College London, UK George Karypis, University of Minnesota, USA Vipin Kumar, University of Minnesota, USA Marta Kwiatkowska, University of Oxford, UK Angelo Lucia, University of Rhode Island, USA George Michailidis, University of Florida, USA Kaisa Miettinen, University of Jyväskylä, Finland Stephen Muggleton, Imperial College London, UK Panos Pardalos, University of Florida, USA Jan Peters, Technische Universitaet Darmstadt & Max-Planck Institute for Intelligent Systems, Germany Tomaso Poggio, MIT, USA Andrey Raygorodsky, Moscow Institute of Physics and Technology, Russia Mauricio G. C. Resende, Amazon.com Research and University of Washington Seattle, Washington, USA Raniero Romagnoli, CTO Almawave, Italy Ruslan Salakhutdinov, Carnegie Mellon University, USA, and AI Research at Apple Maria Schuld, Xanadu & University of KwaZulu-Natal, South Africa Vincenzo Sciacca, Almawave, Italy My Thai, University of Florida, USA Richard E. Turner, Department of Engineering, University of Cambridge, UK Ruth Urner, York University, Toronto, Canada Isabel Valera, Saarland University, Saarbrücken & Max Planck Institute for Intelligent Systems, Tübingen, Germany SPECIAL SESSIONS: https://lod2021.icas.cc/special-sessions/ *) Special Session on "Data Science for Sustainable Cities" Chairs: Alberto Castellini, Alessandro Farinelli, Giuseppe Nicosia, Varun Ojha Contact: alberto.castellini(a)univr.it The amount of data generated nowadays by society, city infrastructures, and digital technologies around us is astonishing. The analysis, modeling and knowledge extraction of/from these data is a key asset for understanding urban environments and improving the efficiency of urban mobility, air quality and other forms of sustainability. This special session provides a platform to share high-quality research ideas related to data science methods and technologies for urban environments, a topic of crucial importance for many Sustainable Development Goals (i.e., SDG 7 on Sustainable Energy and SDG 11 on Sustainable Cities and Communities). Another important goal is to establish a meeting point for researchers in academia and industry who develop methodologies and technologies for data science, machine learning and artificial intelligence with specific applications in smart and sustainable cities. Analytics for smart growth and effective infrastructure A selection of the best papers accepted for the presentation at the special session will be invited to submit an extended version for publication on Frontiers in Sustainable Cities ( https://www.frontiersin.org/journals/sustainable-cities#) *) Special Session on AI for Sustainability We welcome contributions on AI for Sustainable Development, AI for Sustainable Urban Mobility, AI for Food Security, AI to fight Deforestation, cutting-edge technology AI to create Inclusive and Sustainable development that leaves no one behind. *) Special Session on AI to help to fight Climate Change AI is a new tool to help us better manage the impacts of climate change and protect the planet. AI can be a “game-changer” for climate change and environmental issues. AI refers to computer systems that “can sense their environment, think, learn, and act in response to what they sense and their programmed objectives,” World Economic Forum report, Harnessing Artificial Intelligence for the Earth. We accept papers/short papers/talks at the intersection of climate change, AI, machine learning and data science. AI, Machine Learning and Data Science can be invaluable tools both in reducing greenhouse gas emissions and in helping society adapt to the effects of climate change. We invite submissions using AI, Machine Learning and/or Data Science to address problems in climate mitigation/adaptation including but not limited to the following topics: * Industrial Session Chairs: Giovanni Giuffrida – Neodata. * Special Session on Explainable Artificial Intelligence Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence applications. https://robotics.sciencemag.org/content/4/37/eaay7120 * Special Session on Multi-Objective Optimization (MOO) & Multi Criteria Decision Aiding (MCDA) * The 7 Special Sessions on Machine Learning Multi-Task Learning Reinforcement Learning Deep Learning Generative Adversarial Networks Deep Neuroevolution Networks with Memory Learning from Less Data and Building Smaller Models * The 7 Special Session on Data Science and Artificial Intelligence Simulation Environments to understand how AI Systems Learn Chatbots and Conversational Agents Data Science at Scale & Data in the Cloud Urban Informatics & Data-Driven Modelling of Complex Systems Data-centric Engineering Data Security, Traceability of Information & GDPR Economic Data Science BEST PAPER AWARD: Springer sponsors the LOD 2021 Best Paper Award with a cash prize of 1,000 Euro. https://lod2021.icas.cc/best-paper-award/ PROGRAM COMMITTEE: 500+ confirmed PC members! Breaking the record of the last edition of LOD! https://lod2021.icas.cc/program-committee/ VENUE: https://lod2021.icas.cc/venue/ “ESCAPE THE HURRYING WORLD – The loveliest spot that man hath ever found…” Escape to the Lake District, England – a UNESCO World Heritage site – and you’ll find it’s easy to share William Wordsworth’s delight in the area. The Wordsworth Hotel & Spa (****) Address: Grasmere, Ambleside, Lake District, Cumbria, LA22 9SW, England, UK Phone: +44-1539-435592 Email: enquiry(a)thewordsworthhotel.co.uk Web: www.thewordsworthhotel.co.uk ACCOMMODATION: https://lod2021.icas.cc/accommodation/ ACTIVITIES: https://lod2021.icas.cc/activities/ Best WALKS in the Lake District National Park: https://lod2021.icas.cc/walks/ Submit your research work today! https://easychair.org/conferences/?conf=lod2021 See you in the beautiful Lake District - UK in October! Best regards, LOD 2021 Organizing Committee Past Editions https://lod2021.icas.cc/past-editions/ LOD 2020, The Sixth International Conference on Machine Learning, Optimization and Big Data Certosa di Pontignano – Siena – Tuscany – Italy. Nature Springer – LNCS volumes 12565 and 12566. LOD 2019, The Fifth International Conference on Machine Learning, Optimization and Big Data Certosa di Pontignano – Siena – Tuscany – Italy. Nature Springer – LNCS volume 11943. LOD 2018, The Fourth International Conference on Machine Learning, Optimization and Big Data Volterra – Tuscany – Italy. Nature Springer – LNCS volume 11331. MOD 2017, The Third International Conference on Machine Learning, Optimization and Big Data Volterra – Tuscany – Italy. Springer – LNCS volume 10710. MOD 2016, The Second International Workshop on Machine learning, Optimization and big Data Volterra – Tuscany – Italy. Springer – LNCS volume 10122. MOD 2015, International Workshop on Machine learning, Optimization and big Data Taormina – Sicily – Italy. Springer – LNCS volume 9432. Past Keynote Speakers: https://lod2021.icas.cc/past-keynote-speakers/ https://www.facebook.com/groups/2236577489686309/ https://twitter.com/TaoSciences https://www.linkedin.com/groups/12092025/ * Apologies for multiple copies. Please forward to anybody who might be interested * lod(a)icas.cc https://lod2021.icas.cc LOD2021 Poster: https://lod2021.icas.cc/wp-content/uploads/sites/16/2021/04/poster-LOD-2021… --

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Live e-Lecture by Prof. Anibal Ollero: “Toward efficient and safe intelligent aerial robotics and aerial manipulation”, 4th May 2021 17:00-18:00 CET. Upcoming AIDA AI excellence lectures
by Ioanna Koroni 26 Apr '21

26 Apr '21

Dear AI scientist/engineer/student/enthusiast, Prof. Anibal Ollero (University Seville, Spain), a prominent AI & Robotics researcher internationally, will deliver the e-lecture: ‘Toward efficient and safe intelligent aerial robotics and aerial manipulation’, on Tuesday 4th May 2021 17:00-18:00 CET (8:00-9:00 am PST), (12:00 am-1:00am CST), see details in: <http://www.i-aida.org/ai-lectures/> http://www.i-aida.org/ai-lectures/ You can join for free using the zoom link: https://authgr.zoom.us/j/91092951412 & Passcode: 148148 The <http://www.i-aida.org/> International AI Doctoral Academy (AIDA), a joint initiative of the European R&D projects <https://ai4media.eu/> AI4Media, ELISE <https://www.elise-ai.eu/> , Humane AI Net <https://www.humane-ai.eu/> , TAILOR <https://tailor-network.eu/> , VISION <https://www.vision4ai.eu/> , currently in the process of formation, is very pleased to offer you top quality scientific lectures on several current hot AI topics. Lectures will be offered alternatingly by: Top highly-cited senior AI scientists internationally or Young AI scientists with promise of excellence (AI sprint lectures) Lectures are typically held once per week, Tuesdays 17:00-18:00 CET (8:00-9:00 am PST), (12:00 am-1:00am CST). Attendance is free. Other upcoming lectures: 1. Prof. John Shawe-Taylor (University College London, UK), 18th May 2021 17:00 – 18:00 CET. More lecture infos in: <http://www.i-aida.org/future-lectures/> http://www.i-aida.org/future-lectures/ These lectures are disseminated through multiple channels and email lists (we apologize if you received it through various channels). If you want to stay informed on future lectures, you can register in the email lists AIDA email list <https://lists.auth.gr/sympa/info/aida> and <https://lists.auth.gr/sympa/info/cvml> CVML email list. Best regards Profs. M. Chetouani, P. Flach, B. O’Sullivan, I. Pitas, N. Sebe -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus

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[SIGKDD Workshop on Mining and Learning from Time Series 2021]: Call for papers
by Sanjay Purushotham 22 Apr '21

22 Apr '21

CFP Webpage: https://kdd-milets.github.io/milets2021/#call -------------------------------------------------------------- 7th SIGKDD Workshop on Mining and Learning from Time Series (MiLeTS) 2021 Aug 14th, 2021 - KDD Virtual Conference https://kdd-milets.github.io/milets2021/ -------------------------------------------------------------- ---------------- KEY DATES ---------------- Paper Submission Deadline: May 20th, 2021, 11:59PM Alofi Time Author Notification: June 10th, 2021 Camera Ready Version: June 24th, 2021 Workshop: August 14th, 2021 ------------------------------------------------- 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 2021 EasyChair website: https://easychair.org/conferences/?conf=milets2021. *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 listed 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, 2021, 11:59PM Alofi Time Author Notification: June 10th, 2021 Camera Ready Version: June 24th, 2021 Workshop: August 14th, 2021 ------------------------------- Organizing Committee ------------------------------- Sanjay Purushotham University of Maryland, Baltimore County Yaguang Li Google Zhengping Che Didi Chuxing -------------------------- 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.

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CFP - KDD 2021 Workshop on Misinformation and Misbehavior Mining on the Web (MIS2)
by Kai Shu 21 Apr '21

21 Apr '21

Workshop website: http://claws.cc.gatech.edu/mis2-kdd2021Call for papers The web is a space for all, allowing participating individuals to read, publish and share content openly. Despite its groundbreaking benefits in areas such as education and communication, it has also become a breeding ground for misbehavior and misinformation: any individual can reach thousands of people on the web near-instantaneously, purporting whatever they wish while also being shielded by anonymity. This capacity has led to rampant increases in misbehavior and misinformation vectors, via harassment, online scams, spread of propaganda, hate speech, deceptive reviews and more. Such issues have severe implications on both social and financial fronts. The study of misinformation and misbehavior mining has become focal for researchers across many subfields of data, computational and social sciences, including network science, machine learning, cybersecurity, privacy, natural language processing, human computer interaction and more. MIS2 @ KDD 2021 provides a venue for researchers working in, or adjacent to these diverse areas to coalesce around central and timely topics in online misinformation and misbehavior, and present recent advances in research. - Topics of interest include (but are not limited to): - Empirical characterization of false information - Measuring real world and online impact - Deception in misinformation and misbehavior - Reputation manipulation - Measuring economic, ideological, and other rationale behind creation - Rationale behind spread and success - Targets or victims of misbehavior and misinformation - Effect of echo chambers, personalization, confirmation bias, and other socio-psychological and technological phenomenon - Detection methods using graphs, text, behavior, image, video, and audio analysis - Adversarial analysis of misbehavior and misinformation - Prevention and mitigation techniques, tools, and countermeasures - Theoretical and/or empirical modeling of spread - Visualizing spread - Anonymity, security, and privacy aspects of data collection - Usable security in misbehavior detection - Ethics, privacy, transparency, fairness, and biases in current tools and techniques - Case studies Paper Submission We encourage submissions with both academic and industrial motivations, of the following types: - Novel research papers in full or short length - Demo papers - Survey papers - Comparison papers of existing methods and tools - Work-in-progress papers - Case studies - Extended abstracts - Relevant work that has been recently published (must select to opt out from publication in companion proceedings of the workshop) - Work that will be presented at the main conference of KDD 2021 (the submission should mention that your paper has been accepted at the conference) - We explicitly encourage the submission of preliminary work in the form of extended abstracts (2 pages). All submissions will be peer-reviewed by at least 2 reviewers, and all accepted manuscripts will be presented (virtually) at the workshop. Additionally, accepted papers will be published in the companion proceedings of the KDD conference and ACM digital library, unless the authors choose to opt out from publication. Format Papers must be submitted in PDF according to the new ACM format published in ACM guidelines <http://www.acm.org/publications/proceedings-template>, selecting the generic "sigconf" sample, with a font size no smaller than 9pt. Submissions should be 2 to 8 pages long. No need to anonymize your submission. Submission Link Papers should be submitted via the CMT: https://cmt3.research.microsoft.com/KDDMIS2021 Important Dates - Workshop Paper Submission: June 1st, 2021 - Workshop Paper Notification: June 10th, 2021 - Camera ready deadline: July 1st, 2021 - Workshop date: August 14-18, 2021 Organizers Srijan Kumar, Georgia Institute of Technology Aude Hofleitner, Facebook Meng Jiang, University of Notre Dame Neil Shah, Snap Kai Shu, Illinois Institute of Technology ContactPlease direct all questions to kdd_mis2(a)googlegroups.com

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