Workshop Date: Sunday August 14, 2022 EDT. Malicious attacks for ML models to identify their vulnerability in black-box/real-world scenarios. For example, failures in IoT can result in infrastructure disruptions, and failures in autonomous cars can lead to congestion and crashes. 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. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. We also welcome submissions that are currently under consideration in such archival venues. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. We will specifically invite participants of the DSTC10 tasks, track organizers, and authors of accepted papers in the general technical track. Frontiers in Big Data, accepted, 2021. Deep Generative Model for Periodic Graphs. 25, 2022: We have announced Call for Nominations: , Mar. The review process will be single blind. The program consists of poster sessions for accepted papers, and invited and spotlight talks. Adverse event detection by integrating Twitter data and VAERS. DOI:https://doi.org/10.1145/3339823. We invite submission of papers describing innovative research and applications around the following topics. Yevgeniy Vorobeychik (Washington University in St. Louis), Bruno Sinopoli (Washington University in St. Louis), Jinghan Yang (Washington University in St. Louis), Bo Li (UIUC), Atul Prakash (University of Michigan), Supplemental Workshop site:https://jinghany.github.io/trase2022/. We encourage authors to contact the organizers to discuss possible overlap. Submissions are limited to 4 pages, not including references. I recommend highly motivated students to reach out to me way earlier than the admission deadline, and figure out a research project project with me, with the goal of a publication. "GA-based principal component selection for production performance estimation in mineral processing." Integration of Deep learning and Constraint programming. Journal of Biomedical Semantics, (impact factor: 1.845), 2018, accepted. Algorithms for secure and privacy-aware machine learning for AI. This cookie is set by GDPR Cookie Consent plugin. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. The impact of robustness assurance on other AI ethics principles: RAISA will also explore aspects related to ethical AI that overlap and interact with robustness concerns, including security, fairness, privacy, and explainability. As Artificial Intelligence (AI) begins to impact our everyday lives, industry, government, and society with tangible consequences, it becomes increasingly important for a user to understand the reasons and models underlying an AI-enabled systems decisions and recommendations. Data mining systems and platforms, and their efficiency, scalability, security and privacy. Papers that introduce new theoretical concepts or methods, help to develop a better understanding of new emerging concepts through extensive experiments, or demonstrate a novel application of these methods to a domain are encouraged. It is well-known that deep learning techniques that were disruptive for Euclidean data such as images or sequence data such as text are not immediately applicable to graph-structured data. The growing popularity of NAS methods demonstrates the communitys hunger for better ways of choosing or evolving network architectures that are well-matched to the problem at hand. a concise checklist by Prof. Eamonn Keogh (UC Riverside). However, you may visit "Cookie Settings" to provide a controlled consent. Submission instructions will be available at the workshop web page. Consult the list of programs available in the next session. "Multi-resolution Spatial Event Forecasting in Social Media." Other submissions will be evaluated by a committee based on their novelty and insights. This thread already has a best answer. 2020. Can AI achieve the same goal without much low-level supervision? Data science is the practice of deriving insights from data, enabled by statistical modeling, computational methods, interactive visual analysis, and domain-driven problem solving. Bioinformatics (Impact Factor: 6.937), accepted, 2022. Innovation, Service, and Rising Star Awards. It highlights the importance of declarative languages that enable such integration for covering multiple formalisms at a high-level and points to the need for building a new generation of ML tools to help domain experts in designing complex models where they can declare their knowledge about the domain and use data-driven learning models based on various underlying formalisms. We received 38 paper submissions and accepted 23 of them. with other vehicles via vehicular communication systems (e.g., dedicated short range communication (DSRC), vehicular ad hoc networks (VANETs), long term evolution (LTE), and 5G/6G mobile networks) for cooperation. While most work on XAI has focused on opaque learned models, this workshop also highlights the need for interactive AI-enabled agents to explain their decisions and models. Scientists and engineers in diverse domains are increasingly relying on using AI tools to accelerate scientific discovery and engineering design. If you are interested, please send a short email to rl4edorg@gmail.com and we can add you to the invitee list. Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph. The main goal of the dialog system technology challenge (DSTC) workshop is to share the result of five main tracks of the tenth dialog system technology challenge (DSTC10). The paper submissions must be in pdf format and use the AAAI official templates. These approaches make it possible to use a tremendous amount of unlabeled data available on the web to train large networks and solve complicated tasks. We expect 50-65 people in the workshop. Template guidelines are here:https://www.acm.org/publications/proceedings-template. Welcome to the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2022), which will be held in Chengdu, China on May 16-19, 2022. KDD 2022 is a dual-track conference that provides distinct programming in research and applied data science. While progress has been impressive, we believe we have just scratched the surface of what is capable, and much work remains to be done in order to truly understand the algorithms and learning processes within these environments. Finally, there is an increasing interest in AI in moving beyond traditional supervised learning approaches towards learning causal models, which can support the identification of targeted behavioral interventions. Scott E. Fahlman, School of Computer Science, Carnegie Mellon University (sef@cs.cmu.edu), Edouard Oyallon, Sorbonne Universit LIP6 (Edouard.oyallon@lip6.fr), Dean Alderucci, School of Computer Science, Carnegie Mellon University, (dalderuc@cs.cmu.edu). The cookie is used to store the user consent for the cookies in the category "Other. How to do good research, Get it published in SIGKDD and get it cited! [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. After seventh highly successful events, the eighth Symposium on Visualization in Data Science (VDS) will be held at a new venue, ACM KDD 2022 as well as IEEE VIS 2022. While the research community is converging on robust solutions for individual AI models in specific scenarios, the problem of evaluating and assuring the robustness of an AI system across its entire life cycle is much more complex. 1, 2022: Call For Paper: The Undergraduate Consortium at SIGKDD 2022 is available at, Mar. job seekers, employers, recruiters and job agents. Meta-learning models from various existing task-specific AI models. We are in a conversation with some publishers once they confirm, we will announce accordingly. We cordially welcome researchers, practitioners, and students from academia and industry who are interested in understanding and discussing how data scarcity and bias can be addressed in AI to participate. Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. How can we make AI-based systems more ethically aligned? Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. However, workshop organizers may set up any archived publication mechanism that best suits their workshop. The AAAI template https://aaai.org/Conferences/AAAI-22/aaai22call/ should be used for all submissions. RES: A Robust Framework for Guiding Visual Explanation. Their results will be submitted in either a short paper or poster format. This topic also encompasses techniques that augment or alter the network as the network is trained. Deep Geometric Neural Networks for Spatial Interpolation. While we are planning an in-person workshop to be held at AAAI-22, we aim to accommodate attendees who may not be able to travel to Vancouver by allowing participation via live virtual invited talks and virtual poster sessions. Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. Zirui Xu, Fuxun Xu, Liang Zhao, and Xiang Chen. Qiang Yang, Hong Kong University of Science and Technology/ WeBank, China, (qyang@cse.ust.hk ), Sin G. Teo, Institute for Infocomm Research, Singapore (teosg@i2r.a-star.edu.sg), Han Yu, Nanyang Technological University, Singapore (han.yu@ntu.edu.sg), Lixin Fan, WeBank, China (lixinfan@webank.com), Chao Jin, Institute for Infocomm Research, Singapore (jin_chao@i2r.a-star.edu.sg), Le Zhang, University of Electronic Science and Technology of China (zhangleuestc@gmail.com), Yang Liu, Tsinghua University, China (liuy03@air.tsinghua.edu.cn), Zengxiang Li, Digital Research Institute, ENN Group, China (lizengxiang@enn.cn), Workshop site:http://federated-learning.org/fl-aaai-2022/. The 21st Web Conference (WWW 2022), (Acceptance Rate: 17.7%), accepted. Junxiang Wang, Fuxun Yu, Xiang Chen, and Liang Zhao. anomaly detection, and ensemble learning. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Recently self-supervised approaches for speech/audio processing are also gaining attention. Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu. Disease Contact Network. Andrew White, University of RochesterDr. Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao. Researchers from related domains are invited to submit papers on recent advanced technologies, resources, tools and challenges for VTU. Welcome to PAKDD2022. We will end the workshop with a panel discussion by invited speakers from different fields to enlist future directions. In the coronavirus era, requiring many schools to move to online learning, the ability to give feedback at scale could provide needed support to teachers. We send a public call and we assume the workshop will be of interest to many AAAI main conference audiences; we expect 50 participants. Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng and Liang Zhao. The post-lunch session will feature one long talk, two short talks, and a poster session. [Bests of ICDM]. Award for Artificial Intelligence for the Benefit of Humanity, Patrick Henry Winston Outstanding Educator Award, A Report to ARPA on Twenty-First Century Intelligent Systems, The Role of Intelligent Systems in the National Information Infrastructure, Code of Conduct for Conferences and Events, Request to Reproduce Copyrighted Materials, AAAI Conference on Artificial Intelligence, W1: Adversarial Machine Learning and Beyond, W2: AI for Agriculture and Food Systems (AIAFS), W6: AI in Financial Services: Adaptiveness, Resilience & Governance, W7: AI to Accelerate Science and Engineering (AI2ASE), W8: AI-Based Design and Manufacturing (ADAM) (Half-Day), W9: Artificial Intelligence for Cyber Security (AICS)(2-Day), W10: Artificial Intelligence for Education (AI4EDU), W11: Artificial Intelligence Safety (SafeAI 2022)(1.5-Day), W12: Artificial Intelligence with Biased or Scarce Data, W13: Combining Learning and Reasoning: Programming Languages, Formalisms, and Representations (CLeaR), W14: Deep Learning on Graphs: Methods and Applications (DLG-AAAI22), W15: DE-FACTIFY :Multi-Modal Fake News and Hate-Speech Detection, W16: Dialog System Technology Challenge (DSTC10), W17: Engineering Dependable and Secure Machine Learning Systems (EDSMLS 2022) (Half-Day), W18: Explainable Agency in Artificial Intelligence, W19: Graphs and More Complex Structures for Learning and Reasoning (GCLR), W21: Human-Centric Self-Supervised Learning (HC-SSL), W22: Information-Theoretic Methods for Causal Inference and Discovery (ITCI22), W23: Information Theory for Deep Learning (IT4DL), W25: Knowledge Discovery from Unstructured Data in Financial Services (Half-Day), W26: Learning Network Architecture during Training, W27: Machine Learning for Operations Research (ML4OR) (Half-Day), W28: Optimal Transport and Structured Data Modeling (OTSDM), W29: Practical Deep Learning in the Wild (PracticalDL2022), W30: Privacy-Preserving Artificial Intelligence, W31: Reinforcement Learning for Education: Opportunities and Challenges, W32: Reinforcement Learning in Games (RLG), W33: Robust Artificial Intelligence System Assurance (RAISA) (Half-Day), W34: Scientific Document Understanding (SDU) (Half-Day), W35: Self-Supervised Learning for Audio and Speech Processing, W36: Trustable, Verifiable and Auditable Federated Learning, W38: Trustworthy Autonomous Systems Engineering (TRASE-22), W39: Video Transcript Understanding (Half-Day), https://openreview.net/group?id=AAAI.org/2022/Workshop/AdvML, https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, https://easychair.org/conferences/?conf=aaai-2022-workshop, https://rail.fzu.edu.cn/info/1014/1064.htm, https://aaai.org/Conferences/AAAI-22/aaai22call/, https://sites.google.com/view/aaaiwfs2022, https://www.aaai.org/Publications/Templates/AuthorKit22.zip, https://openreview.net/group?id=AAAI.org/2022/Workshop/ADAM, https://easychair.org/conferences/?conf=aics22, https://cmt3.research.microsoft.com/AIBSD2022, https://aibsdworkshop.github.io/2022/index.html, https://openreview.net/forum?id=6uMNTvU-akO, https://easychair.org/conferences/?conf=dlg22, https://deep-learning-graphs.bitbucket.io/dlg-aaai22/, https://cmt3.research.microsoft.com/DSTC102022, https://dstc10.dstc.community/calls_1/call-for-workshop-papers, https://easychair.org/my/conference?conf=edsmls2022, https://sites.google.com/view/edsmls-2022/home, https://sites.google.com/view/eaai-ws-2022/call, https://sites.google.com/view/eaai-ws-2022/topic, https://sites.google.com/view/gclr2022/submissions, https://cmt3.research.microsoft.com/AAAI2022HCSSL/Submission/Index, https://cmt3.research.microsoft.com/ITCI2022, https://easychair.org/conferences/?conf=it4dl, https://easychair.org/conferences/?conf=imlaaai22, https://sites.google.com/view/aaai22-imlw, https://easychair.org/conferences/?conf=kdf22, Learning Network Architecture During Training, https://cmt3.research.microsoft.com/OTSDM2022, https://cmt3.research.microsoft.com/PracticalDL2022, https://cmt3.research.microsoft.com/PPAI2022, https://easychair.org/conferences/?conf=rl4edaaai22, https://sites.google.com/view/raisa-2022/, https://sites.google.com/view/sdu-aaai22/home, https://cmt3.research.microsoft.com/SAS2022, https://easychair.org/conferences/?conf=fl-aaai-22, http://federated-learning.org/fl-aaai-2022/, https://cmt3.research.microsoft.com/TAIH2022, https://easychair.org/conferences/?conf=trase2022, https://easychair.org/my/conference?conf=vtuaaai2022, Symposium on Educational Advances in Artificial Intelligence (EAAI-22), Conference on Innovative Applications of Artificial Intelligence (IAAI-22). Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. Attendance is virtual and open to all. There is now a great deal of interest in finding better alternatives to this scheme. Accepted submissions will be notified latest by August 7th, 2022. This proposed workshop will build upon successes and learnings from last years successful AI for Behavior Change workshop, and will focus on on advances in AI and ML that aim to (1) design and target optimal interventions; (2) explore bias and equity in the context of decision-making and (3) exploit datasets in domains spanning mobile health, social media use, electronic health records, college attendance records, fitness apps, etc. AAAI is pleased to present the AAAI-22 Workshop Program. Detailed information could be found on the website of the workshop. Ferdinando Fioretto (Syracuse University), Emma Frejinger (Universit de Montral), Elias B. Khalil (University of Toronto), Pashootan Vaezipoor (University of Toronto).