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The full-day workshop will start with an opening remark followed by long research paper presentations in the morning. Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. 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. Objectives of ADAM include outlining the main research challenges in this area, cross-pollinating collaborations between AI researchers and domain experts in engineering design and manufacturing, and sketching open problems of common interest. In this 2nd instance of GCLR (Graphs and more Complex structures for Learning and Reasoning) workshop, we will focus on various complex structures along with inference and learning algorithms for these structures. Submissions tackling new problems or more than one of the aforementioned topics simultaneously are encouraged. Paper Submission:November 12, 2021, 11:59 pm (anywhere on earth) Author Notification: December 3, 2021Full conference:February 22 March 1, 2022Workshop:February 28 March 1, 2022. NOTE: May 19: Notification. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. Topics of interest include, but are not limited to: Paper submissions will be in two formats: full paper (8 pages) and position paper (4 pages): The submission website ishttps://easychair.org/conferences/?conf=trase2022. Papers must be in PDF format, in English, and formatted according to the AAAI template. We expect ~60 attendees. This is especially the case for non-traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities with the sheer size and ever-increasing growth and change rate of their data. Our intent is to facilitate new AI/ML advances for core engineering design, simulation, and manufacturing. 5, pp. "Multi-Task Learning for Spatio-Temporal Event Forecasting." Accepted papers will be published in the workshop proceedings. 2022. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. This workshop aims to bring together researchers from AI and diverse science/engineering communities to achieve the following goals: 1) Identify and understand the challenges in applying AI to specific science and engineering problems2) Develop, adapt, and refine AI tools for novel problem settings and challenges3) Community-building and education to encourage collaboration between AI researchers and domain area experts. Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. "A Topic-focused Trust Model for Twitter." All submissions will be peer-reviewed. 10, pp. Invited speakers, committee members, authors of the research paper, and the participants of the shared task are invited to attend. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. 4. Comparison or integration of self-supervised learning methods and other semi-supervised and transfer learning methods in speech and audio processing tasks. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). Through invited talks and presentations by the participants, this workshop will bring together current advances in Network Science as well as Machine Learning, and set the stage for continuing interdisciplinary research discussions. Aug 11, 2022: Get early access for registration at L Street Bridge, Washington DC Convention Center, from 4-6 pm, Saturday, August 13. Autonomous vehicles can share their detected information (e.g., traffic signs, collision events, etc.) Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. The program of the workshop will include invited talks, paper presentations and a panel discussion. Combating fake news is one of the burning societal crises. It does not store any personal data. Deadline in . Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. All papers will be peer-reviewed, single-blinded (i.e., please include author names/affiliations/email addresses on your first page). The cookie is used to store the user consent for the cookies in the category "Analytics". The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 20%=174/870), short paper, to appear, 2022. Novel methods to learn from scarce/sparse, or heterogenous, or multimodal data. The post-lunch session will feature a second keynote talk, two invited talks. Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia and Charu Aggarwal, "Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding", 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. RLG is a full-day workshop. We invite thought-provoking submissions and talks on a range of topics in these fields. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. "Robust Regression via Heuristic Hard Thresholding". 2022. 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. Attendance is open to all, subject to any room occupancy constraints. Submissions will be accepted via the Easychair submission website. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. "Online and Distributed Robust Regressions under Adversarial Data Corruption", in Proceedings of the IEEE International Conference on Data Mining (ICDM 2017) , regular paper; (acceptance rate: 9.25%), pp. Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji and Charu Aggarwal. InProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2013), demo track, pp. These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. Feature Constrained Multi-Task Learnings for Event Forecasting in Social Media." Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu. It is anticipated that this will be an in-person workshop, subject to changing travel restrictions and health measures. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. The format is the standard double-column AAAI Proceedings Style. Transfer learning methods for business document reading and understanding. NOTE: Mandatory abstract deadline: 2022-08-08 Deadline: AAAI 157. have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). This workshop aims to bring researchers from these diverse but related fields together and embark on interesting discussions on new challenging applications that require complex system modeling and discovering ingenious reasoning methods. We welcome the submissions in the following two formats: The submissions should adhere to theAAAI paper guidelines. 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. 1953-1970, Oct. 2017. These lead to security considerations: (1) securing personal health information, genetic material, intellectual property, and digital health records, (2) balancing privacy rights and data ownership concerns in solutions using network and mobile data, (3) defending AI for biology use cases to deter automated attacks at scale. Are you sure you want to create this branch? 639-648, Nov 2015. Share. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. The 11th International Conference on Learning Representations (ICLR 2023), accepted. 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. What techniques and approaches can be used to detect and effectively manage similar scenarios in the future? Some existing research also presents that there is a trade-off between the robustness and accuracy of deep learning models. Countdowns to conference deadlines in the field of autonomous driving. We encourage long papers, short papers and demo papers. The submitted papers written in English must be in PDF format according to the AAAI camera ready style. Papers will be peer-reviewed and selected for oral and/or poster presentations at the workshop. ACM, New York, NY, USA, 10 pages. Jan 13, 2022: Notification. Supplemental Workshop site:https://rl4ed.org/aaai2022/index.html. Information-theoretic approaches provide a novel set of tools that can expand the scope of classical approaches to causal inference and discovery problems in a variety of applications. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. in Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), research track, (acceptance rate: 19.4%), Sydney, Australia, pp. Knowledge Discovery and Data Mining is an interdisciplinary area focusing Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. The final schedule will be available in November. This one-day workshop will bring concentrated discussions on self-supervision for the field of speech/audio processing via keynote speech, invited talks, contributed talks and posters based on community-submitted high-quality papers, and the result representation of SUPERB and Zero Speech challenge. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. The paper submissions must be in pdf format and use the AAAI official templates. information bottleneck principle). "How events unfold: spatiotemporal mining in social media." Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Babies learn their first language through listening, talking, and interacting with adults. Algorithms and theories for explainable and interpretable AI models. These cookies will be stored in your browser only with your consent. Participation of researchers from a wide variety of areas is encouraged, including Data Science, Machine Learning, Symbolic AI, Mathematical programming, Constraint Optimization, Reinforcement Learning, Dynamic control and Operations Research. How can we characterize or evaluate AI systems according to their potential risks and vulnerabilities? Full (8 pages) and short (4 pages, work in progress) papers, AAAI style. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. These challenges and issues call for robust artificial intelligence (AI) algorithms and systems to help. The robust development and assured deployment of AI systems: Participants will discuss how to leverage and update common software development paradigms, e.g., DevSecOps, to incorporate relevant aspects of system-level AI assurance. 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. 205-214, San Francisco, California, Aug 2016. A fundamental problem in the use of artificial neural networks is that the first step is to guess the network architecture. Submissions of technical papers can be up to 7 pages excluding references and appendices. Deep learning and statistical methods for data mining. Fang Jin, Wei Wang, Liang Zhao, Edward Dougherty, Yang Cao, Chang-Tien Lu, and Naren Ramakrishnan. Please note that the KDD Cup workshop will haveno proceedingsand the authors retainfull rightsto submit or post the paper at any other venue. We welcome attendance from individuals who do not have something theyd like to submit but who are interested in RL4ED research. 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 Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao. "Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design", 28th International Conference on Field Programmable Logic and Applications (FPL 2019), (acceptance rate: 18%), Barcelona, Spain, accepted. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. Washington DC, USA. [slides] Summer. In spite of substantial research focusing on discovery from news, web, and social media data, its applications to datasets in professional settings such as financial filings and government reports, still present huge challenges. Despite gratifying achievements that have demonstrated the great potential and bright development prospect of introducing AI in education, developing and applying AI technologies to educational practice is fraught with its unique challenges, including, but not limited to, extreme data sparsity, lack of labeled data, and privacy issues. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. It will start with a 60-minute mini-tutorial covering the basics of RL in games, and will include 2-4 invited talks by prominent contributors to the field, paper presentations, a poster session, and will close with a discussion panel. Xiaojie Guo, Lingfei Wu, Liang Zhao. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. 2022. Merge remote-tracking branch 'origin/master', 2. [Bests of ICDM], Zheng Zhang and Liang Zhao. We welcome full paper submissions (up to 8 pages, excluding references or supplementary materials). Xiaojie Guo, Yuanqi Du, Liang Zhao. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. We welcome submissions of long (max. Reasons include: (1) a lack of certification of AI for security, (2) a lack of formal study of the implications of practical constraints (e.g., power, memory, storage) for AI systems in the cyber domain, (3) known vulnerabilities such as evasion, poisoning attacks, (4) lack of meaningful explanations for security analysts, and (5) lack of analyst trust in AI solutions. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 20%=174/870), short paper, to appear, 2022. Neural Networks, (impact factor: 8.05), accepted. 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. Submissions will undergo double blind review. and deep learning techniques (e.g. 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. A message will appear on your application form if there is a risk that the time required to process the application and to send the answer, in addition to the time you will need to acquire study permits, will be too long for you to arrive for the beginning of the session. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . Integration of probabilistic inference in training deep models. August 14-18, 2022. If these formalities are not completed in time, you will have to file a new application at a later date. Yuyang Gao, Giorgio Ascoli, Liang Zhao. 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. Zirui Xu, Fuxun Xu, Liang Zhao, and Xiang Chen. How can we develop solid technical visions and new paradigms about AI Safety? CVPR 11 deadline . In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. Registration Opens: Feb 02 '22 02:00 PM UTC: Registration Cancellation Refund Deadline: Apr 18 '22(Anywhere on Earth) Paper Submissions Abstract Submission Deadline: Sep 29 '21 12:00 AM UTC: Paper Submission deadline: Oct 06 '21 12:00 AM . Qingzhe Li, Liang Zhao, Jessica Lin and Yi-ching Lee. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond. Send this CFP to us by mail: cfp@ourglocal.org. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Authors of accepted papers will be invited to participate. Neurocomputing (Impact Factor: 5.719), accepted. arXiv preprint arXiv:2207.09542 (2022). Would you like to mark this message as the new best answer? Half day event featuring a panel, invited and keynote speakers and presentations selected through a CFP. This is a 1-day workshop involving talks by pioneer researchers from respective areas, poster presentations, and short talks of accepted papers. ), Graduate (master's, specialized graduate diploma (DESS), etc. By entering your email, you consent to receive communications from UdeM. 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. 105, no. Liang Zhao, Feng Chen, and Yanfang Ye. 2020. Liang Zhao, Olga Gkountouna, and Dieter Pfoser. Submissions must be formatted in the AAAI submission format (https://www.aaai.org/Publications/Templates/AuthorKit22.zip) All submissions should be done electronically via EasyChair. Like other systems, ML systems must meet quality requirements. 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! Computer Communications, (impact factor: 3.34), Elsevier, vo. Advances in complex engineering systems such as manufacturing and materials synthesis increasingly seek artificial intelligence/machine learning (AI/ML) solutions to enhance their design, development, and production processes. Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu. Knowledge Discovery and Data Mining. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. Integration of declarative and procedural domain knowledge in learning. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. VDS@VIS Submission Deadline:Thur., July 14th, 2022, 5:00 pm PDT, VDS@VIS Author Notification:Thur., August 25th, 2022, 5:00 pm PDT, VDS@KDD Submission Deadline:Thur., May 26th June 2nd, 2022, 5:00 pm PDT, VDS@KDD Author Notification:Mon., June 20th, 2022, 5:00 pm PDT. ADMM for Efficient Deep Learning with Global Convergence. 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. A tag already exists with the provided branch name. For instance, advanced driver assistance systems and autonomous cars have been developed based on AI techniques to perform forward collision warning, blind spot monitoring, lane departure warning systems, traffic sign recognition, traffic safety, infrastructure management and congestion, and so on. 1503-1512, Aug 2015. 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. The last few years have seen the rapid development of mathematical methods for modeling structured data coming from biology, chemistry, network science, natural language processing, and computer vision applications. Innovation, Service, and Rising Star Awards. Federated learning (FL) is one promising machine learning approach that trains a collective machine learning model using sharing data owned by various parties. We invite paper submission with a focus that aligns with the goals of this workshop. The post-launch session includes the invited talks, shared task winners presentations, and a panel discussion on the resources, findings, and upcoming challenges. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. These challenges are widely studied in enterprise networks, but there are many gaps in research and practice as well as novel problems in other domains. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. [Call for papers] KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, CFP: IJCAI 2021 Reinforcement Learning for Intelligent Transportation Systems Workshop, Second Workshop on Marketplace Innovation. In recent years, various information theoretic principles have also been applied to different deep learning related AI applications in fruitful and unorthodox ways. Typically, we receive around 40~60 submissions to each previous workshop. The final schedule will be available in November. The workshop will be organized as a full day meeting. Disentangled Dynamic Graph Deep Generation, SIAM International Conference on Data Mining (SDM 2021), (acceptance rate: 21.3%), accepted. Yuyang Gao, Lingfei Wu, Houman Homayoun, and Liang Zhao. Geoinformatica, (impact factor: 2.392), Volume 20, Issue 4, pp 765-795, Oct 2016. 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. Checklist for Revising a SIGKDD Data Mining Paper, How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering, https://researcher.watson.ibm.com/researcher/view_group.php?id=144, IEEE International Conference on Big Data (, AAAI Conference on Artificial Intelligence (, IEEE International Conference on Data Engineering (, SIAM International Conference on Data Mining (, Pacific-Asia Conference on Knowledge Discovery and Data Mining (, ACM SIGKDD International Conference on Knowledge discovery and data mining (, European Conference on Machine learning and knowledge discovery in databases (, ACM International Conference on Information and Knowledge Management (, IEEE International Conference on Data Mining (, ACM International Conference on Web Search and Data Mining (, 18.4% (181/983, research track), 22.5% (112/497, applied data science track), 59.1% (107/181, research track), 35.7% (40/112, applied data science track), 17.4% (130/748, research track), 22.0% (86/390, applied data science track), 49.2% (64/130, research track), 41.9% (36/86, applied data science track), 18.1% (142/784, research track), 19.9% (66/331, applied data science track), 49.3% (70/142, research track), 60.1% (40/66, applied data science track), 18.5% (194/1046, overall), 9.1% (95/?, regular paper), ?% (99/?, short paper), 19.8% (188/948, overall), 8.9% (84/?, regular paper), ?% (104/?, short paper), 19.9% (155/778, overall), 9.3% (72/?, regular paper), ?% (83/?, short paper), 19.6% (178/904, overall), 8.6% (78/?, regular paper), ?% (100/?, short paper), 19.6% (202/1031, long paper), 22.7% (107/471, short paper), 21.8% (38/174m applied research), 17% (147/826, long paper), 23% (96/413, short paper), 25% (demo), 34% (industry paper), Short papers are presented at poster sessions, 20% (171/855, long paper), 28% (119/419, short paper), 38% (30/80, demo paper), 23% (160/701, long paper), 24% (55/234, short paper), 54 extended short papers (6 pages), 26% (94/354, research track), 26% (37/143, applied ds track), 15% (23/151, journal track), 27.8% (164/592, overall), 9.8% (58/592, long presentation), 18.1% (107/592, regular), 28.2% (129/458, overall), 9.8% (45/458, long presentation), 18.3% (84/458, regular), 29.6% (91/307, overall), 12.7% (39/307, long presentation), 16.9% (52/307, regular), 40.4% (34/84, long presentation), 59.5% (50/84, short presentation)^, 16.3% (84/514 in which 3 papers are withdrawn/rejected after the acceptance), 28.4% (23/81, long presentation), 71.6% (58/81, short presentation)^, 30% (24/80, long presentation), 70% (56/80, short presentation)^, 29.8% (20/67, long presentation), 70.2% (47/67, short presentation)^, 53.8% (21/39, long presentation), 46.2% (18/39, short presentation)^. ICLR 2022 Meeting Dates The Tenth annual conference is held Mon. In addition, any other work on dialog research is welcome to the general technical track. Liang Zhao, Junxiang Wang, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan. However, workshop organizers may set up any archived publication mechanism that best suits their workshop. Yuanqi Du, Xiaojie Guo, Yinkai Wang, Amarda Shehu, Liang Zhao. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. This workshop brings together researchers from diverse backgrounds with different perspectives to discuss languages, formalisms and representations that are appropriate for combining learning and reasoning. Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment. 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).