All the submissions should be anonymous. 10, pp. Workshop URL:https://rail.fzu.edu.cn/info/1014/1064.htm, Prof. Chi-Hua ChenEmail: chihua0826@gmail.comPostal address: No.2, Xueyuan Rd., Fuzhou, Fujian, ChinaTelephone: +86-18359183858. Characterization of fundamental limits of causal quantities using information theory. a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette). We will also select some of the best posters for spotlight talks (2 minutes each). Recently developed tools and cutting-edge methodologies coming from the theory of optimal transport have proved to be particularly successful for these tasks. 2022. Make sure your desired study programs are open for admission in the session when you would like to start your studies. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. Long Beach, California, USA . Deadlines are shown in America/Los_Angeles time. AI for infrastructure management and congestion. The workshop will focus on the application of AI to problems in cyber-security. Benchmarks to reliably evaluate attacks/defenses and measure the real progress of the field. Modern surveillance systems employ tools and techniques from artificial intelligence and machine learning to monitor direct and indirect signals and indicators of disease activities for early, automatic detection of emerging outbreaks and other health-relevant patterns. 4 pages), and position (max. RLG is a full-day workshop. In recent years, we have seen examples of general approaches that learn to play these games via self-play reinforcement learning (RL), as first demonstrated in Backgammon. It leverages many emerging privacy-preserving technologies (SMC, Homomorphic Encryption, differential privacy, etc.) Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. Papers should be up to 4 pages in length (excluding references) formatted using the AAAI template. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. Deep Graph Learning for Circuit Deobfuscation. Countdowns to conference deadlines in the field of autonomous driving. OARS-KDD2022: KDD 2022 Workshop on Online and Adaptive Recommender Systems Washington DC, DC, United States, August 15, 2022 Topics: data science artificial intelligence recommender system recommendation KDD 2022 Workshop on Online and Adaptive Recommender Systems (OARS) Call For Papers ================== We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). Accepted submissions will be notified latest by August 7th, 2022. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. 1799-1808. There is a need for the research community to develop novel solutions for these practical issues. https://doi.org/10.1007/s10707-019-00376-9. Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework. Martin Michalowski, PhD, FAMIA (Co-chair), University of Minnesota; Arash Shaban-Nejad, PhD, MPH (Co-chair), The University of Tennessee Health Science Center Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics; Simone Bianco, PhD (Co-chair), IBM Almaden Research Center; Szymon Wilk, PhD, Poznan University of Technology; David L. Buckeridge, MD, PhD, McGill University; John S. Brownstein, PhD, Boston Childrens Hospital, Workshop URL:http://w3phiai2022.w3phi.com/. If you are interested, please send a short email to rl4edorg@gmail.com and we can add you to the invitee list. Information theoretic quantities (entropy, mutual information, divergence) estimation, Information theoretic methods for out-of-domain generalization and relevant problems (such as robust transfer learning and lifelong learning), Information theoretic methods for learning from limited labelled data, such as few-shot learning, zero-shot learning, self-supervised learning, and unsupervised learning, Information theoretic methods for the robustness of DNNs in AI systems, The explanation of deep learning models (in AI systems) with information-theoretic methods, Information theoretic methods in different AI applications (e.g., NLP, healthcare, robotics, finance). 4 pages) papers describing research at the intersection of AI and science/engineering domains including chemistry, physics, power systems, materials, catalysis, health sciences, computing systems design and optimization, epidemiology, agriculture, transportation, earth and environmental sciences, genomics and bioinformatics, civil and mechanical engineering etc. Accepted submissions will have the option of being posted online on the workshop website. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, and Chang-Tien Lu. We also welcome submissions that are currently under consideration in such archival venues. Please note that the KDD Cup workshop will have no proceedings and the authors retain full rights to submit or post the paper at any other venue. Public health authorities and researchers collect data from many sources and analyze these data together to estimate the incidence and prevalence of different health conditions, as well as related risk factors. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. Papers that are under review at another conference or journal are acceptable for submission at this workshop, but we will not accept papers that have already been accepted or published at a venue with formal proceedings (including KDD 2022). "Misinformation Propagation in the Age of Twitter." The format is the standard double-column AAAI Proceedings Style. KDD 2022. The topics of interest include but are not limited to: Theoretical and Computational Optimal Transport: Optimal Transport-Driven Machine Learning: Optimal Transport-Based Structured Data Modeling: The full-day workshop will start with two long talks and one short talk in the morning. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Datasets and Benchmarks Track, accepted. Previous healthcare-related workshops focus on how to develop AI methods to improve the accuracy and efficiency of clinical decision-making, including diagnosis, treatment, triage. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices. The goal of the inaugural HC-SSL workshop is to highlight and facilitate discussions in this area and expose the attendees to emerging potentials of SSL for human-centric representation learning, and promote responsible AI within the context of SSL. The papers have to be submitted through EasyChair. Novel ML-accelerated optimization for conceptual/detailed system design. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. We will use double-blind reviewing. 1, Sec. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. The objective of this workshop is to discuss the winning submissions of the Submissions to the Amazon KDD Cup 2022 issingle-blind (author names and affiliations should be listed). We encourage long papers, short papers and demo papers. Adverse event detection by integrating Twitter data and VAERS. The acceptance decisions will take in account novelty, technical depth and quality, insightfulness, depth, elegance, practical or theoretical impact, reproducibility and presentation. In decision-making domains as wide-ranging as medication adherence, vaccination uptakes, college enrollment, retirement savings, and energy consumption, behavioral interventions have been shown to encourage people towards making better choices. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. The 19th International Conference on Data Mining (ICDM 2019), long paper, (acceptance rate: 9.08%), Beijing, China. Registration information will be mailed directly to all invited participants in December. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Hierarchical Incomplete Multisource Feature Learning for Spatiotemporal Event Forecasting. in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), research track (acceptance rate: 18.2%), San Francisco, California, pp. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. We invite researchers to submit either full-length research papers (8 pages) or extended abstracts (2 pages) describing novel contributions and preliminary results, respectively, to the topics above; a more extensive list of topics is available on the Workshop website. This workshop has no archival proceedings. Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, Girish Chowdhary (University of Illinois, Urbana Champaign), Baskar Ganapathysubramanian (Iowa State University; contact: baskarg@iastate.edu), George Kantor (Carnegie Mellon University), Soumyashree Kar (Iowa State University), Koushik Nagasubramanian (Iowa State University), Soumik Sarkar (Iowa State University), Katia Sycara (Carnegie Mellon University), Sierra Young (North Carolina State University), Alina Zare (University of Florida, Gainesville), Supplemental workshop site:https://aiafs-aaai2022.github.io/. A primary reason for this is the inherent long-tailed nature of our world, and the need for algorithms to be trained with large amounts of data that includes as many rare events as possible. Saliency-Augmented Memory Completion for Continual Learning. We especially welcome research from fields including but not limited to AI, human-computer interaction, human-robot interaction, cognitive science, human factors, and philosophy. Can AI achieve the same goal without much low-level supervision? We invite the submission of papers with 4-6 pages. In addition to the keynote and presentations of accepted works, the workshop will include both a general discussion session on defining and addressing the key challenges in this area , and a lightning tutorial session that will include brief overviews and demos of relevant tools, including open source frameworks such as Ecole. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. "Efficient Global String Kernel with Random Features: Beyond Counting Substructures", In the Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019), research track (acceptance rate: 14.2%), accepted, Alaska, USA, Aug 2019. We invite thought-provoking submissions and talks on a range of topics in these fields. in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. ACM, 2014. This half day workshop will focus on research into the use of AI techniques to extract knowledge from unstructured data in financial services. Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. The official dates for submitting an application are detailed below, but see the exact deadline posted on the Description Page for the program of study. Computer Science and Engineering, INESC-ID, IST Ulisboa, Lisbon, Portugal currently at Sorbonne University, Paris, France silvia.tulli@gaips.inesc-id.pt), Prashan Madumal (Science and Information Systems, University of Melbourne, Parkville, Australia pmathugama@student.unimelb.edu.au), Mark T. Keane (School of Computer Science, University College Dublin, Dublin, Ireland mark.keane@ucd.ie), David W. Aha (Navy Center for Applied Research in AI, Naval Research Laboratory, Washington, DC, USA david.aha@nrl.navy.mil), Adam Johns (Drexel University, Philadelphia, PA USA), Tathagata Chakraborti (IBM Research AI, Cambridge, MA USA), Kim Baraka (VU University Amsterdam, Netherlands), Isaac Lage (Harvard University, Cambridge, MA USA), David Martens (University of Antwerp, Belgium), Mohamed Chetouani (Sorbonne Universit, Paris, France), Peter Flach (University of Bristol, United Kingdom), Kacper Sokol (University of Bristol, United Kingdom), Ofra Amir (Technion, Haifa, Israel), Dimitrios Letsios (Kings College London, London, United Kingdom), Supplemental workshop site:https://sites.google.com/view/eaai-ws-2022/topic. 639-648, Nov 2015. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. CVPR 11 deadline . Colin Camerer (California Institute of Technology), Susan Murphy (Harvard University). All papers must be submitted in PDF format using the AAAI-22 author kit. in Proceedings of the 24st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), research track (acceptance rate: 18.4%), London, United Kingdom, Aug 2018, accepted. System reports will be presented during poster sessions. The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. . 2022. ML4OR will place particular emphasis on: (1) ML methodologies for enhancing traditional OR algorithms for integer programming, combinatorial optimization, stochastic programming, multi-objective optimization, location and routing problems, etc. You can optionally export all deadlines to Google Calendar or .ics . Please note that the KDD Cup workshop will haveno proceedingsand the authors retainfull rightsto submit or post the paper at any other venue. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. Deep Generative Model for Periodic Graphs. Knowledge Discovery and Data Mining. Zitao Liu (main contact) , TAL Education Group, liuzitao@tal.com, http://www.zitaoliu.com, Jiliang Tang (Michigan State University, tangjili@msu.edu, https://www.cse.msu.edu/~tangjili/), Lihan Zhao (TAL Education Group, zhaolihan@tal.com), and Xiao Zhai (TAL Education Group, zhaixiao@tal.com), Workshop URL:http://ai4ed.cc/workshops/aaai2022. A Systematic Survey on Deep Generative Models for Graph Generation. IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 24.31), accepted. We will accept both original papers up to 8 pages in length (including references) as well as position papers and papers covering work in progress up to 4 pages in length (not including references).Submission will be through Easychair at the AAAI-22 Workshop AI4DO submission site, Professor Bistra Dilkina (dilkina@usc.edu), USC and Dr. Segev Wasserkrug, (segevw@il.ibm.com), IBM Research, Prof. Andrea Lodi (andrea.lodi@cornell.edu), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (dharmash@us.ibm.com), IBM Research. 2, no. We will include a panel discussion to close the workshop, in which the audience can ask follow up questions and to identify the key AI challenges to push the frontiers in Chemistry. Alan Yuille (Professor, Johns Hopkins University); Hao Su (Assistant Professor, UC San Diego); Rongrong Ji (Professor, Xiamen University); Xianglong Liu (Professor, Beihang University); Jishen Zhao (Associate Professor, UC San Diego); Tom Goldstein (Associate Professor, University of Maryland); Cihang Xie (Assistant Professor, UC Santa Cruz); Yisen Wang (Assistant Professor, Peking University); Bohan Zhuang (Assistant Professor, Monash University), Haotong Qin (Beihang University), Yingwei Li (Johns Hopkins University), Ruihao Gong (SenseTime Research), Xinyun Chen (UC Berkeley), Aishan Liu (Beihang University), Xin Dong (Harvard University), Jindong Guo (University of Munich), Yuhang Li (Yale University), Yiming Li (Tsinghua University), Yifu Ding (Beihang University), Mingyuan Zhang (Nanyang Technological University), Jiakai Wang (Beihang University), Jinyang Guo (University of Sydney), Renshuai Tao (Beihang University), Workshop site:https://practical-dl.github.io/. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. "Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling." All papers will be peer reviewed, single-blinded. 625-634, New Orleans, US, Dec 2017. But opting out of some of these cookies may affect your browsing experience. Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. All submissions will be peer-reviewed. Generative Deep Learning for Macromolecular Structure and Dynamics, Current Opinion in Structural Biology, (impact factor: 7.108), Section on Theory and Simulation/Computational Methods 67: 170-177, 2021 accepted. Self-supervised learning (SSL) has shown great promise in problems involving natural language and vision modalities. At least three research trends are informing insights in this field. ACM Transactions on Spatial Algorithms and Systems (TSAS), 5, 3, Article 19 (September 2019), 28 pages. Viliam Lisy (Czech Technical University in Prague, viliam.lisy@fel.cvut.cz), Noam Brown (Facebook AI Research, noambrown@fb.com), Martin Schmid (DeepMind, mschmid@google.com), Supplemental Workshop site:http://aaai-rlg.mlanctot.info/. KDD 2023 KDD '23 ​ ​ ​ August 6-10, 2023. The workshop invites contribution to novel methods, innovations, applications, and broader implications of SSL for processing human-related data, including (but not limited to): In addition to the above, papers that consider the following are also invited: Manuscripts that fit only certain aspects of the workshop are also invited. "EMBERS at 4 years:Experiences operating an Open Source Indicators Forecasting System." Estimate of the audience size: 400-500 attendees (based on the number of attendees in previous DLG workshops in KDD19, AAAI20, KDD20 and AAAI21). algorithms applied to the above topics: deep learning, reinforcement learning, multi-armed bandits, causal inference, mathematical programming, and stochastic optimization. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. All papers will be peer-reviewed, single-blinded (i.e., please include author names/affiliations/email addresses on your first page). Because of the time needed to complete the formalities for entering Canada and Quebec, the admission period for international applicants ends several weeks before the session begins. Paper Submission Deadline: May 26, 2022 Author Notification: June 20, 2022 Camera Ready: July 9, 2022 Workshop: August . Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji and Charu Aggarwal. Advances in AI technology, particularly perception and planning, have enabled unprecedented advances in autonomy, with autonomous systems playing an increasingly important role in day-to-day lives, with applications including IoT, drones, and autonomous vehicles. While classical security vulnerabilities are relevant, ML techniques have additional weaknesses, some already known (e.g., sensitivity to training data manipulation), and some yet to be discovered. We allow papers that are concurrently submitted to or currently under review at other conferences or venues. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), (Acceptance Rate: 25.6%), to appear, 2022. The final schedule will be available in November. Second, psychological experiments in laboratories and in the field, in partnership with technology companies (e.g., using apps), to measure behavioral outcomes are being increasingly used for informing intervention design. This date takes priority over those shown below and could be extended for some programs. IEEE Transactions on Knowledge and Data Engineerings (TKDE), (impact factor: 6.977), accepted. California, United Stes. Methods for learning network architecture during training, including Incrementally building neural networks during training, new performance benchmarks for the above. Malicious attacks for ML models to identify their vulnerability in black-box/real-world scenarios. We invite participants to submit papers by the 12th of November, based on but not limited to, the following topics: RL in various formalisms: one-shot games, turn-based, and Markov games, partially-observable games, continuous games, cooperative games; deep RL in games; combining search and RL in games; inverse RL in games; foundations, theory, and game-theoretic algorithms for RL; opponent modeling; analyses of learning dynamics in games; evolutionary methods for RL in games; RL in games without the rules; search and planning; and online learning in games. Short papers 10m presentation and 5m discussion. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. Some will be selected for spotlight talks, and some for the poster session. The biomedical space has seen a flurry of activity recently, and cyber criminals have amplified their efforts with health-related phishing attacks, spreading misinformation, and intruding into health infrastructure. 1145/3394486.3403221. This workshop covers (but not limited to) the following topics: , It is a one day workshop and includes: invited talks, interactive discussions, paper presentations, shared task presentations, poster session etc. We are excited to continue promoting innovation in self-supervision for the speech/audio processing fields and inspiring the fields to contribute to the general machine learning community. to protect data owner privacy in FL. We welcome submissions of long (max. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Researchers from related domains are invited to submit papers on recent advanced technologies, resources, tools and challenges for VTU. By entering your email, you consent to receive communications from UdeM. Securing personal information, genomics, and intellectual property, Adversarial attacks and defenses on biomedical datasets, Detecting and preventing spread of misinformation, Usable security and privacy for digital health information, Phishing and other attacks using health information, Novel use of biometrics to enhance security, Machine learning (including RL) security and resiliency, Automation of data labeling and ML techniques, Operational and commercial applications of AI, Explanations of security decisions and vulnerability of explanations.
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