Papers will be submitted to OpenReview system: Waiting for approval,https://openreview.net/forum?id=6uMNTvU-akO, Workshop Chair:Parisa Kordjamshidi, +1-2174187004, [email protected], Organizing Committee:Parisa Kordjamshidi (Michigan State University, [email protected]), Behrouz Babaki (Mila/HEC Montreal, [email protected]), Sebastijan Dumani (KU Leuven, [email protected]), Alex Ratner (University of Washington, [email protected]), Hossein Rajaby Faghihi (Michigan State University, [email protected]), Hamid Karimian (Michigan State University, [email protected]), Organizing Committee:Dan Roth (University of Pennsylvania, [email protected]) and Guy Van Den Broeck (University of California Los Angeles, [email protected]), Supplemental workshop site:https://clear-workshop.github.io. Zitao Liu (main contact) , TAL Education Group, [email protected], http://www.zitaoliu.com, Jiliang Tang (Michigan State University, [email protected], https://www.cse.msu.edu/~tangjili/), Lihan Zhao (TAL Education Group, [email protected]), and Xiao Zhai (TAL Education Group, [email protected]), Workshop URL:http://ai4ed.cc/workshops/aaai2022. It has gained popularity in some domains such as image classification, speech recognition, smart city, and healthcare. Spatiotemporal Innovation Center Team. KDD 2022. Complex systems are often characterized by several components that interact in multiple ways among each other. The trustworthy issues of clinical AI methods were not discussed. Big Data 2022 December 13-16, 2022. We are in a conversation with some publishers once they confirm, we will announce accordingly. New theory and fundamentals of AI-aided design and manufacturing. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. Oral Paper (Top 5% among the accepted papers). Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2020), (acceptance rate: 20.6%), accepted. The mission of the TRASE workshop is to bring together researchers from multiple engineering disciplines, including Computer Science, and Computer, Mechanical, Electrical, and Systems Engineering, who focus their energies in understanding both specific TRASE subproblems, such as perception, planning, and control, as well as robust and reliable end-to-end integration of autonomy. Checklist for Revising a SIGKDD Data Mining Paper: These cookies ensure basic functionalities and security features of the website, anonymously. ETA (expected time-of-arrival) prediction. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. In nearly all applications, reliability, safety, and security of such systems is a critical consideration. 507-516, Singapore, Nov 2017. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. An increasing world population, coupled with finite arable land, changing diets, and the growing expense of agricultural inputs, is poised to stretch our agricultural systems to their limits. 2022. Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. Scott E. Fahlman, School of Computer Science, Carnegie Mellon University ([email protected]), Edouard Oyallon, Sorbonne Universit LIP6 ([email protected]), Dean Alderucci, School of Computer Science, Carnegie Mellon University, ([email protected]). In other words, many existing FL solutions are still exposed to various security and privacy threats. A fundamental problem in the use of artificial neural networks is that the first step is to guess the network architecture. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . System reports will be presented during poster sessions. 4, Roosevelt Rd., Taipei, TaiwanAffiliation: National Taiwan UniversityPhone: +1-412-465-0130Email: [email protected], Paul CrookAddress: 1 Hacker Way, Menlo Park, CA, USAAffiliation: FacebookPhone: +1-650-885-0094Email: [email protected], DSTC 10 home:https://dstc10.dstc.community/homeDSTC 10 CFPs:https://dstc10.dstc.community/calls_1/call-for-workshop-papers. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. Saliency-Augmented Memory Completion for Continual Learning. All papers must be submitted in PDF format, using the AAAI-22 author kit. 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. 2022. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. Transfer learning methods for business document reading and understanding. 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. All questions about submissions should be emailed to [email protected], AmazonKDDCup2022: KDD Cup 2022 Workshop: ESCI Challenge for Improving Product Search, Washington DC, DC, United States, August 17, 2022, https://easychair.org/conferences/?conf=amazonkddcup2022, https://www.acm.org/publications/proceedings-template. All submissions must be anonymous and conform to AAAI standards for double-blind review. Document structure and layout learning and recognition. 5 (2014): 1447-1459. Track 1 covers the issues and algorithms pertinent to general online marketplaces as well as specific problems and applications arising from those diverse domains, such as ridesharing, online retail, food delivery, house rental, real estate, and more. To view them in conference website timezones, click on them. Half day event featuring a panel, invited and keynote speakers and presentations selected through a CFP. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. Deadlines are shown in America/Los_Angeles time. Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong. KDD 2022 : Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. Neural Networks, (impact factor: 8.05), accepted. Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. The AAAI template https://aaai.org/Conferences/AAAI-22/aaai22call/ should be used for all submissions. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. RES: A Robust Framework for Guiding Visual Explanation. KDD 2023 August 06-10, 2023. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. 17th International Workshop on Mining and Learning with Graphs. However, the quality of audio and video content shared online and the nature of speech and video transcripts pose many challenges to the existing natural language processing. The submitted contributions will be peer-reviewed by the Program Committee, and preference will be given to high-quality original and relevant work to the Document Intelligence topics. Some existing research also presents that there is a trade-off between the robustness and accuracy of deep learning models. Computer Science and Engineering, INESC-ID, IST Ulisboa, Lisbon, Portugal currently at Sorbonne University, Paris, France [email protected]), Prashan Madumal (Science and Information Systems, University of Melbourne, Parkville, Australia [email protected]), Mark T. Keane (School of Computer Science, University College Dublin, Dublin, Ireland [email protected]), David W. Aha (Navy Center for Applied Research in AI, Naval Research Laboratory, Washington, DC, USA [email protected]), 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. Xiaojie Guo, Yuanqi Du, Liang Zhao. IEEE Computer (impact factor: 3.564), vo. Combating fake news is one of the burning societal crises. The academic session will focus on most recent research developments on GNNs in various application domains. Microsoft Research CMT: https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/ or https://aka.ms/di-2022, Workshop registration will be processed with the main KDD 2022 conference: https://kdd.org/kdd2022/, Standard ACM Conference Proceedings Template, Conflict of Interest Policy for ACM Publications, https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/, Second Document Intelligence Workshop @ KDD 2021, First Document Intelligence Workshop @ NeurIPS 2019, Hamid Motahari, Nigel Duffy, Paul Bennett, and Tania Bedrax-Weiss. Submissions that are already accepted or under review for another conference or already accepted for a journal are not accepted. Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self, Rupinder Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Chris Kuhlman, Achla Marathe, Liang Zhao, Ting Hua, Feng Chen, et al.. "'Beating the news' with EMBERS:forecasting civil unrest using open source indicators." In addition, any other work on dialog research is welcome to the general technical track. Our topics of interest span over prediction, planning, and decision problems for online marketplaces, including but not limited to. Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Self-supervised learning utilizes proxy supervised learning tasks, for example, distinguishing parts of the input signal from distractors, or generating masked input segments conditioned on the unmasked ones, to obtain training data from unlabeled corpora. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Datasets and Benchmarks Track, accepted. 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. 40, no. To push forward the research on acronym understanding in scientific text, we propose two shared tasks on acronym extraction (i.e., recognizing acronyms and phrases in text) and disambiguation (i.e., finding the correct expansion for an ambiguous acronym). Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. December, 09-12, 2022. "Bridging the gap between spatial and spectral domains: A survey on graph neural networks." Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. SIGMOD 2022 adheres to the ACM Policy Against Harassment. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. Position papers (4 pages in length for main content + 2 pages for references in AAAI format): we are seeking position papers that advocate for a particular approach or set of approaches, or present an overview of a promising relevant research area. 41-50, New Orleans, US, Dec 2017. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. 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. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. Junxiang Wang, Hongyi Li, Liang Zhao. 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. How can we characterize or evaluate AI systems according to their potential risks and vulnerabilities? ; (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. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. Deep learning and statistical methods for data mining. Yuyang Gao, Lingfei Wu, Houman Homayoun, and Liang Zhao. This workshop has no archival proceedings. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. 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. [Bests of ICDM]. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. 2022. Deep Graph Spectral Evolution Networks for Graph Topological Evolution. 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. Make sure your desired study programs are open for admission in the session when you would like to start your studies. 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. We invite submission of papers describing innovative research on all aspects of knowledge discovery and data science, ranging from theoretical foundations to novel models and algorithms for data science problems in science, business, medicine, and engineering. Positive applications of adversarial ML, i.e., adversarial for good. 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. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. In this workshop, we aim to address the trustworthy issues of clinical AI solutions. 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). Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. The research contributions may discuss technical challenges of reading and interpreting business documents and present research results. Proceedings of the ACM on Human-Computer Interaction (CSCW 2022), to appear, 2022. The submitted papers written in English must be in PDF format according to the AAAI camera ready style. 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. Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, and Chang-Tien Lu. Cesa Salaam (Howard University, USA), Hwanhee Lee (Seoul National University, South Korea), Jaemin Cho (University of North Carolina at Chapel Hill, USA), Jielin Qiu (Carnegie Mellon University, USA), Joseph Barrow (University of Maryland, US), Mengnan Du (Texas A&M University, USA), Minh Van Nguyen (University of Oregon, USA), Nicole Meister (Princeton University, USA), Sajad Sotudeh Gharebagh (Georgetown University, USA), Sampreeth Chebolu (University of Houston, USA), Sarthak Jain (Northeastern University, USA),Shufan Wang (University of Massachusetts Amherst, USA), Supplemental Workshop site:https://vtuworkshop.github.io/2022/, https://research.ibm.com/haifa/Workshops/AAAI-22-AI4DO/.