kdd 2022 deadline kdd 2022 deadline

2022. of Graz), Cynthia Rudin (Duke Univ.) In particular, we encourage papers covering late-breaking results and work-in-progress research. AI is one of these transformative technologies that is now achieving great successes in various real-world applications and making our life more convenient and safer. Integration of AI-based approaches with engineering prototyping and manufacturing. How to do good research, Get it published in SIGKDD and get it cited! chess, checkers). SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints. Checklist for Revising a SIGKDD Data Mining Paper: Researchers from related domains are invited to submit papers on recent advanced technologies, resources, tools and challenges for VTU. AI System Robustness: participants will consider techniques for detecting and mitigating vulnerabilities at each of the processing stages of an AI system, including: the input stage of sensing and measurement, the data conditioning stage, during training and application of machine learning algorithms, the human-machine teaming stage, and during operational use. 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. Submissions are limited to a maximum of four (4) pages, including all content and references, and must be in PDF format. What safety engineering considerations are required to develop safe human-machine interaction? Proceedings of the IEEE (impact factor: 9.237), vol. Research efforts and datasets on text fact verification could be found, but there is not much attention towards multi-modal or cross-modal fact-verification. The goal of this workshop is to connect researchers in self-supervision inside and outside the speech and audio fields to discuss cutting-edge technology, inspire ideas and collaborations, and drive the research frontier. GraphGT: Machine Learning Datasets for Deep Graph Generation and Transformation. Contrast Pattern Mining in Paired Multivariate Time Series of Controlled Driving Behavior Experiment. Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, and Liang Zhao. DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. The accepted papers are allowed to be submitted to other conference venues. It is a forum to bring attention towards collecting, measuring, managing, mining, and understanding multimodal disinformation, misinformation, and malinformation data from social media. We plan to invite 2-4 keynote speakers from prestigious universities and leading industrial companies. The program of the workshop will include invited talks, paper presentations and a panel discussion. December 2020, July 21: Clarified that the workshop this year will be held, June 20: Paper notification is now extended to, Paper reviews are underway! Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. Hyperparameters such as the number of layers, the number of nodes in each layer, the pattern of connectivity, and the presence and placement of elements such as memory cells, recurrent connections, and convolutional elements are all manually selected. Oct. 24, 2021: The KDD2022 website is LIVE! In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Combating fake news is one of the burning societal crises. All these changes require novel solutions, and the AI community is well-positioned to provide both theoretical- and application-based methods and frameworks. Transformations in many fields are enabled by rapid advances in our ability to acquire and generate data. We invite paper submission with a focus that aligns with the goals of this workshop. 2022. We will use double-blind reviewing. 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. Adversarial attacking deep learning systems, Robust architectures against adversarial attacks, Hardware implementation and on-device deployment, Benchmark for evaluating model robustness, New methodologies and architectures for efficient and robust deep learning, December 3, 2021 Acceptance Notification, Applications of privacy-preserving AI systems, Differential privacy: theory and applications, Distributed privacy-preserving algorithms, Privacy preserving optimization and machine learning, Privacy preserving test cases and benchmarks. the 56th Design Automation Conference (DAC 2019), accepted, (acceptance rate: 20%), Las Vegas, US, 2019. Liang Gou, Bosch Research (IEEE VIS liaison), Claudia Plant, University of Vienna (KDD liaison), Alvitta Ottley, Washington University, St. Louis, Junming Shao, University of Electronic Science and Technology of China, Visualization in Data Science (VDS at ACM KDD and IEEE VIS), Visualization in Data Science (VDS at ACM KDD and IEEE VIS). We invite thought-provoking submissions and talks on a range of topics in these fields. We encourage authors to contact the organizers to discuss possible overlap. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. Rabat, Morocco . Recent years have witnessed growing interest in human and AI systems with the increasing realisation that machines can indeed meet objectives specified but the real question becomes have they been given the right objectives. Novel ML-accelerated optimization for conceptual/detailed system design. Xiaojie Guo and Liang Zhao. We allow both short (2-4 pages) and long papers (6-8 pages) papers. Yuanqi Du*, Shiyu Wang* (co-first author), Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang, Aishwarya Varala, Abhinav Angirekula, Liang Zhao. This date takes priority over those shown below and could be extended for some programs. Aug 11, 2022: Get early access for registration at L Street Bridge, Washington DC Convention Center, from 4-6 pm, Saturday, August 13. Junxiang Wang and Liang Zhao. Knowledge Discovery and Data Mining is an interdisciplinary area focusing upon methodologies and applications for extracting useful knowledge from data [1] . 3, pp. 1, 2022: Call For Paper: The Undergraduate Consortium at SIGKDD 2022 is available at, Mar. It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. applications: ridesharing, online retail, food delivery, house rental, real estate, and more. 76, pp. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. SIGKDD Explorations, Vol. Data mining systems and platforms, and their efficiency, scalability, security and privacy. upon methodologies and applications for extracting useful knowledge from data [1]. Highlights: Government day with NSF, NIH, DARPA, NIST, and IARPA Local industries in the DC Metro Area, including the Amazon's second headquarter New initiatives at KDD 2022: undergraduate research and poster session Early career research day with postdoctoral scholars and assistant professors in a mentoring workshop and panel Workshops and hands-on tutorials on emerging topics Yuyang Gao, Tanmoy Chowdhury (co-first author), Lingfei Wu, Liang Zhao. Novel ML methods in the computational material and physical sciences. In this workshop we would like to focus on a contrasting approach, to learn the architecture during training. Lyle Unga (University of Pennsylvania, ungar@cis.upenn.edu), Rahul Ladhania* (University of Michigan, ladhania@umich.edu, primary contact), Linnea Gandhi (University of Pennsylvania, lgandhi@wharton.upenn.edu), Michael Sobolev (Cornell Tech, michael.sobolev@cornell.edu), Supplemental workshop site:https://ai4bc.github.io/ai4bc22/, For any questions, please reach out to us at ai4behaviorchange at gmail dot com. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." These datasets can be leveraged to learn individuals behavioral patterns, identify individuals at risk of making sub-optimal or harmful choices, and target them with behavioral interventions to prevent harm or improve well-being. Integration of neuro and symbolic approaches. Lastly, learning joint modalities is of interest to both Natural Language Processing (NLP) and Computer Vision (CV) forums. This AAAI-22 workshop on AI for Decision Optimization (AI4DO) will explore how AI can be used to significantly simplify the creation of efficient production level optimization models, thereby enabling their much wider application and resulting business values.The desired outcome of this workshop is to drive forward research and seed collaborations in this area by bringing together machine learning and decision-making from the lens of both dynamic and static optimization models. Despite rapid recent progress, it has proven to be challenging for Artificial Intelligence (AI) algorithms to be integrated into real-world applications such as autonomous vehicles, industrial robotics, and healthcare. San Francisco, USA . We hope this will help bring the communities of data mining and visualization more closely connected. A final tribute was paid on Saturday to former Coalition Avenir Qubec (CAQ) minister Nadine Girault, who died of lung cancer last month at age 63 . Can AI achieve the same goal without much low-level supervision? All the workshop chairs, most of the Committees, and the authors of the accepted papers will attend the workshop also. Your Style Your Identity: LeveragingWriting and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network, The Web Conference (WWW 2019), short paper, (acceptance rate: 20%), accepted, 2019. Short or position papers of up to 4 pages are also welcome. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016), regular paper, (acceptance rate: 8.5%), pp. What are the primary lessons learned from the model failures? Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2021), (acceptance rate: 21.0%), accepted. For example, AI tools are built to ease the workload for teachers. 19-25, 2016. Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. [paper] The academic session will focus on most recent research developments on GNNs in various application domains. Panel discussion: Interactive Q&A session with a panel of leading researchers. We will accept the extended abstracts of the relevant and recently published work too. We allow papers that are concurrently submitted to or currently under review at other conferences or venues. Such systems are better modeled by complex graph structures such as edge and vertex labeled graphs (e.g., knowledge graphs), attributed graphs, multilayer graphs, hypergraphs, temporal/dynamic graphs, etc. Deep Graph Learning for Circuit Deobfuscation. 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. To facilitate KDD related research, we create this repository with: *ICDM has two tracks (regular paper track and short paper track), but the exact statistic is not released, e.g., the split between these two tracks. Integrated syntax and semantic approaches for document understanding. This cookie is set by GDPR Cookie Consent plugin. Although machine learning (ML) approaches have demonstrated impressive performance on various applications and made significant progress for AI, the potential vulnerabilities of ML models to malicious attacks (e.g., adversarial/poisoning attacks) have raised severe concerns in safety-critical applications. Papers will be peer-reviewed and selected for oral and/or poster presentations at the workshop. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. 2020. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. We are in a conversation with some publishers once they confirm, we will announce accordingly. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. "A Topic-focused Trust Model for Twitter." Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting. Submissions will be peer reviewed, single-blinded. https://doi.org/10.1007/s10707-019-00376-9. Topics include but not limited to: Large-scale and novel targeting technologies, Fraud, fairness, explainability and privacy, Intelligent assistants in job hunting and hiring automation, Large-scale and high performing data infrastructure, data analysis and tooling, Economics and causal inference in online jobs marketplace, Large-scale analytics of user behaviors in online jobs marketplace. Adaptive Kernel Graph Neural Network. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. 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. At the same time, multimodal hate-speech detection is an important problem but has not received much attention. Trade-Off between Privacy-Preserving and Explainable Federated Learning Federated Learning Multi-Party Computation, Federated Learning Homomorphic Encryption, Federated Learning Personalization Techniques, Federated Learning Meets Mean-Field Game Theory, Federated Learning-based Corporate Social Responsibility. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. Following this AAAI conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. Deep learning has achieved significant success for artificial intelligence (AI) in multiple fields. Roco Mercado, Massachusetts Institute of Technology. Table identification and extraction from business documents. Fine tuning a neural network is very time consuming and far from optimal. Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2020), (acceptance rate: 20.6%), accepted. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. Theoretical understanding of adversarial ML and its connection to other areas. The accelerated developments in the field of Artificial Intelligence (AI) hint at the need for considering Safety as a design principle rather than an option. Xiaosheng Li, Jessica Lin, Liang Zhao. 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. The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. Workshop Date: Sunday August 14, 2022 EDT. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. At least one author of each accepted submission must register and present the paper at the workshop. Expected attendance is 40-50 people. However, the use of rich data sets also raises significant privacy concerns: They often reveal personal sensitive information that can be exploited, without the knowledge and/or consent of the involved individuals, for various purposes including monitoring, discrimination, and illegal activities. Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. IEEE Computer (impact factor: 3.564), vo. Microsoft's Conference Management Toolkit is a hosted academic conference management system. For research track papers and applied data science track papers. SIAM International Conference on Data Mining (SDM 2022), (Acceptance Rate: 26%), accepted. Deep Graph Transformation for Attributed, Directed, and Signed Networks. 2020. The workshop will include original contributions on theory, methods, systems, and applications of data mining, machine learning, databases, network theory, natural language processing, knowledge representation, artificial intelligence, semantic web, and big data analytics in web-based healthcare applications, with a focus on applications in population and personalized health. The workshop will be a one-day workshop, featuring speakers, panelists, and poster presenters from machine learning, biomedical informatics, natural language processing, statistics, behavior science. ISPRS International Journal of Geo-Information (IJGI), (impact factor: 1.502), 5.10 (2016): 193. 17th International Workshop on Mining and Learning with Graphs. Submissions including full papers (6-8 pages) and short papers (2-4 pages) should be anonymized and follow the AAAI-22 Formatting Instructions (two-column format) at https://www.aaai.org/Publications/Templates/AuthorKit22.zip. Submissions are limited to 4 pages, not including references. At least three research trends are informing insights in this field. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. Modern interface, high scalability, extensive features and outstanding support are the signatures of Microsoft CMT. Submission Site: See the webpagehttps://sites.google.com/view/gclr2022/submissions; for detailed instructions and submission link. Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji and Charu Aggarwal. Integration of Deep learning and Constraint programming. Functional Connectivity Prediction with Deep Learning for Graph Transformation. We especially welcome research from fields including but not limited to AI, human-computer interaction, human-robot interaction, cognitive science, human factors, and philosophy. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Datasets and Benchmarks Track, accepted. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. Paper Submission Deadline: May 26, 2022 Author Notification: June 20, 2022 Camera Ready: July 9, 2022 Workshop: August . This workshop aims to explore and advance the current state of research and practice, including but not limited to the following topics: In addition to the invited talks and the panel discussion on topics related to Document Intelligence, the workshop program will include paper sessions which provides an opportunity to present peer-reviewed work on the topic related to Document Intelligence. These cookies will be stored in your browser only with your consent. This workshop aims to bring together researchers from industry and academia and from different disciplines in AI and surrounding areas to explore challenges and innovations in IML. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. [code] Feng Chen, Baojian Zhou, Adil Alim, Liang Zhao. We received 38 paper submissions and accepted 23 of them. Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data. "Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework",The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. The reproducibility papers include a clarification phase: Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. It further combines academia and industry in a quest for well-founded practical solutions. Deep Graph Spectral Evolution Networks for Graph Topological Evolution. ISBN: 978-981-16-6053-5. SIGSPATIAL Special (invited paper), vo. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. Application fees are not refundable. The KDD 2022 program promises to be the most robust and diverse to date, with keynote presentations, industry-led sessions, workshops, and tutorials spanning a wide range of topics - from data-driven humanitarian mapping and applied data science in healthcare to the uses of artificial intelligence (AI) for climate mitigation and decision . Publication in HC-SSL does not prohibit authors from publishing their papers in archival venues such as NeurIPS/ICLR/ICML or IEEE/ACM Conferences and Journals. Accepted papers will be given the opportunity to present at the spotlight sessions during the workshop. Check the deadlines for submitting your application. The 39th IEEE International Conference on Data Engineering (ICDE 2023), accepted. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. Wang, Shiyu, Yuanqi Du, Xiaojie Guo, Bo Pan, and Liang Zhao. Characterization of fundamental limits of causal quantities using information theory. We will specifically invite participants of the DSTC10 tasks, track organizers, and authors of accepted papers in the general technical track. Counter-intuitive behaviors of ML models will largely affect the public trust on AI techniques, while a revolution of machine learning/deep learning methods may be an urgent need. If you are interested, please send a short email to rl4edorg@gmail.com and we can add you to the invitee list. 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. Track 2 focuses on the state of the art advances in the computational jobs marketplace. Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, "Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation", ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 1.98), accepted, 2019. Adverse event detection by integrating Twitter data and VAERS. "Bridging the gap between spatial and spectral domains: A survey on graph neural networks." Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. However, most models and AI systems are built with conservative operating environment assumptions due to regulatory compliance concerns. Three categories of contributions are sought: full-research papers up to 8 pages; short papers up to 4 pages; and posters and demos up to 2 pages. Liming Zhang, Dieter Pfoser, Liang Zhao. SIGMOD 2022 adheres to the ACM Policy Against Harassment. Submissions are limited to a total of 5 pages for initial submission (up to 6 pages for final camera-ready submission), excluding references or supplementary materials, and authors should only rely on the supplementary material to include minor details that do not fit in the 5 pages. Attendance is open to all; at least one author of each accepted submission must be physically/virtually present at the workshop. There will be live Q&A sessions at the end of each talk and oral presentation. Algorithms and theories for explainable and interpretable AI models. Attendance is open to all. to protect data owner privacy in FL. Self-supervised learning (SSL) has shown great promise in problems involving natural language and vision modalities. sup-port vector machine (SVM), decision tree, random forest, etc.) Attendance is open to all registered participants. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. Even in cases where one is able to collect data, there are inherently many kinds of biases in this process, leading to biased models. ; (2) Deep Learning (DL) approaches that can exploit large datasets, particularly Graph Neural Networks (GNNs) and Deep Reinforcement Learning (DRL); (3) End-to-end learning methodologies that mend the gap between ML model training and downstream optimization problems that use ML predictions as inputs; (4) Datasets and benchmark libraries that enable ML approaches for a particular OR application or challenging combinatorial problems. Advances in IML promise to make AIs more accessible and controllable, more compatible with the values of their human partners and more trustworthy. search, ranking, recommendation, and personalization. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International Junxiang Wang, Junji Jiang, Liang Zhao. The desired LENGTH of the workshop: Full-day (~8 hours). Dynamic Tracking and Relative Ranking of Airport Threats from News and Social Media. An example of the latter is theCascade Correlation algorithm, as well as others that incrementally build or modify a neural network during training, as needed for the problem at hand. Accepted papers are likely to be archived. 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).