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The workshop will be co-located with the KDD 2022 conference at Washington DC Convention Center,Washington D.C., USA onAugust 17th, 2022 at1PM5PM (Eastern Standard Time). Deadlines are shown in America/Los_Angeles time. Submissions that are already accepted or under review for another conference or already accepted for a journal are not accepted. URL: https://sites.google.com/view/kdd22onlinemarketplaces Call For Papers (Submission deadline: June3, 2022) 29, no. "Robust Regression via Heuristic Hard Thresholding". References will not count towards the page limit. The post-lunch session will feature a second keynote talk, two invited talks. The accepted papers will be allocated either a contributed talk or a poster presentation. Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features. Junxiang Wang, Junji Jiang, Liang Zhao. However, theoreticians and practitioners of AI and Safety are confronted with different levels of safety, different ethical standards and values, and different degrees of liability, that force them to examine a multitude of trade-offs and alternative solutions. 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/. Pourya Hoseinip, Liang Zhao, and Amarda Shehu. 2022. Algorithms and theories for trustworthy AI models. For research track papers and applied data science track papers. 1466-1469. Welcome to the home of the 2023 ACM SIGMOD/PODS Conference, to be held in the Seattle metropolitan area, Washington, USA, on June 18 - June 23, 2023. for causal estimation in behavioral science. We allow both short (2-4 pages) and long papers (6-8 pages) papers. This workshop seeks to explore new ideas on AI safety with particular focus on addressing the following questions: Contributions are sought in (but are not limited to) the following topics: To deliver a truly memorable event, we will follow a highly interactive format that will include invited talks and thematic sessions. Creative Commons Attribution-Share Alike 3.0 License, 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, Knowledge Discovery and Data Mining Conference, 22nd ACM SIGKDD international conference on knowledge discovery and data mining, 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 18th ACM SIGKDD Knowledge Discovery and Data Mining, The 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Business documents are central to the operation of all organizations, and they come in all shapes and sizes: project reports, planning documents, technical specifications, financial statements, meeting minutes, legal agreements, contracts, resumes, purchase orders, invoices, and many more. Saliency-Augmented Memory Completion for Continual Learning. There is now a great deal of interest in finding better alternatives to this scheme. ICLR 2022 Meeting Dates The Tenth annual conference is held Mon. 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. Finally, the workshop will welcome papers that describe the release of privacy-preserving benchmarks and data sets that can be used by the community to solve fundamental problems of interest, including in machine learning and optimization for health systems and urban networks, to mention but a few examples. a fantastic tutorial on SIGKDD'09 by Prof. Eamonn Keogh (UC Riverside). Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. Any participant who experiences unacceptable behavior may contact any current member of the SIGMOD Executive Committee, the PODS Executive Committee, DBCares, or this year's D&I co-chairs Pnar Tzn (pito@itu.dk) and Renata Borovica-Gajic (renata.borovica@unimelb.edu.au). Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. Xiaojie Guo, Yuanqi Du, Liang Zhao. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. The third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22) builds on the success of previous years PPAI-20 and PPAI-21 to provide a platform for researchers, AI practitioners, and policymakers to discuss technical and societal issues and present solutions related to privacy in AI applications. The trained models are intended to assign scores to novel utterances, assessing whether they are possible or likely utterances in the training language. The post-lunch session will feature one long talk, two short talks, and a poster session. Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. As for the Kraken, they made one trade a month ago to acquire a seventh defenceman, Jaycob Megna and did nothing else (from 'Kraken remain quiet as NHL trade deadline passes,' The Seattle . These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. Yuyang Gao, Giorgio Ascoli, Liang Zhao. applications: ridesharing, online retail, food delivery, house rental, real estate, and more. Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning. What techniques and approaches can be used to detect and effectively manage similar scenarios in the future? Please note that the KDD Cup workshop will have no proceedings and the authors retain full rights to submit or post the paper at any other venue. Theoretical understanding of adversarial ML and its connection to other areas. 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. KDD 2022. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, and Naren Ramakrishnan. SDU will be a one-day workshop. 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. Each paper will be reviewed by three reviewers in double-blind. Precision agriculture and farm management, Development of open-source software, libraries, annotation tools, or benchmark datasets, Bias/equity in algorithmic decision-making, AI for ITS time-series and spatio-temporal data analyses, AI for the applications of transportation, Applications and techniques in image recognition based on AI techniques for ITS, Applications and techniques in autonomous cars and ships based on AI techniques. The industry session will emphasize practical industrial product developments using GNNs. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. We will receive the paper on the CMT system. 1799-1808. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. Options include pruning a trained network or training many networks automatically. DI@KDD2022 Call for Papers Organization Program Keynote Talk Accepted Papers Call for Papers Document Intelligence Workshop @ KDD 2022 UPDATES August 6: Final versions of the papersare posted! Knowledge Discovery and Data Mining is an interdisciplinary area focusing upon methodologies and applications for extracting useful knowledge from data [1] . ), The workshop will be organized as half-day event with 2 invited speakers, follow by presentation from accepted papers (both ordinary papers, and shared task paper). But opting out of some of these cookies may affect your browsing experience. KDD 2023 KDD '23 ​ ​ ​ August 6-10, 2023. Submission URL:https://easychair.org/my/conference?conf=vtuaaai2022. 2022. This workshop covers (but not limited to) the following topics: , It is a one day workshop and includes: invited talks, interactive discussions, paper presentations, shared task presentations, poster session etc. 2022. 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. iCal Outlook robotics Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting. Declarative languages and differentiable programming. It does not store any personal data. Out of these, around 20~30 papers are accepted. Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu. This cookie is set by GDPR Cookie Consent plugin. a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette). The challenge requires participants to build competitive models for diverse downstream tasks with limited labeled data and trainable parameters, by reusing self-supervised pre-trained networks. 17th International Workshop on Mining and Learning with Graphs. System reports will be presented during poster sessions. In addition, authors can provide an optional one page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. In other words, many existing FL solutions are still exposed to various security and privacy threats. These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. Computers & Electrical Engineering (impact factor: 2.189), vo. Despite the great success of deep neural networks (DNNs) in many artificial intelligence (AI) tasks, they still suffer from limitations, such as poor generalization behavior for out-of-distribution (OOD) data, vulnerability to adversarial examples, and the black-box nature of DNNs. ACM RecSys 2022 will be held in Seattle, USA, from September 18 - 23, 2022. Deep Geometric Neural Networks for Spatial Interpolation. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. KDD is the premier Data Science conference. a concise checklist by Prof. Eamonn Keogh (UC Riverside). A striking feature of much of this recent work is the application of new theoretical and computational techniques for comparing probability distributions defined on spaces with complex structures, such as graphs, Riemannian manifolds and more general metric spaces. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. 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. ACM, 2013. ", ACM Transactions on Spatial Algorithms and Systems (TSAS), (Acceptance Rate: 11%), Volume 2 Issue 4, Acticle No. 1923-1935, 1 Oct. 2020, doi: 10.1109/TKDE.2019.2912187. 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. 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 welcome full paper submissions (up to 8 pages, excluding references or supplementary materials). Time Series Clustering in Linear Time Complexity. 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. Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. Accepted papers are likely to be archived. Authors are invited to send a contribution in the AAAI-22 proceedings format. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. [Best Paper Award]. The topics of interest include but are not limited to: Theoretical and Computational Optimal Transport: Optimal Transport-Driven Machine Learning: Optimal Transport-Based Structured Data Modeling: The full-day workshop will start with two long talks and one short talk in the morning. However, ML systems may be non-deterministic; they may re-use high-quality implementations of ML algorithms; and, the semantics of models they produce may be incomprehensible. We will end the workshop with a panel discussion by invited speakers from different fields to enlist future directions. How can we engineer trustable AI software architectures? The workshop welcomes the submission of work on, but not limited to, the following research directions. Check the CFP for details Deadline: ICDM 2020 . [materials][data]. 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.