kdd 2022 deadline11 Apr kdd 2022 deadline
The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. 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). Unsupervised Deep Subgraph Anomaly Detection. The academic session will focus on most recent research developments on GNNs in various application domains. Deadlines are shown in America/Los_Angeles time. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Encore track papers that have been recently published, or accepted for publication in a conference or journal. New theory and fundamentals of AI-aided design and manufacturing. To adapt SSL frameworks to build effective human-centric deep learning solutions for human-centric data, a number of key challenges and opportunities need to be explored. Transfer learning methods for business document reading and understanding. [materials]. All time are 23:59, AoE (Anywhere on Earth), Hongteng Xu (Renmin University of China, hongtengxu@ruc.edu.cn, main contact), Julie Delon (Universit de Paris, julie.delon@u-paris.fr), Facundo Mmoli (Ohio State University, facundo.memoli@gmail.com), Tom Needham (Florida State University, tneedham@fsu.edu). SIGKDD Explorations, Vol. In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. 4 pages), and position (max. Proceedings of the IEEE (impact factor: 9.237), vol. While classical security vulnerabilities are relevant, ML techniques have additional weaknesses, some already known (e.g., sensitivity to training data manipulation), and some yet to be discovered. We expect ~60 attendees. Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features. While most work on XAI has focused on opaque learned models, this workshop also highlights the need for interactive AI-enabled agents to explain their decisions and models. Sign-regularized multi-task learning. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. VDS will bring together domain scientists and methods researchers (including data mining, visualization, usability and HCI, data management, statistics, machine learning, and software engineering) to discuss common interests, talk about practical issues, and identify open research problems in visualization in data science. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. the 33rd Annual Computer Security Applications Conference (ACSAC 2018), (acceptance rate: 20.1%), San Juan, Puerto Rico, USA, Dec 2018, accepted. Welcome to PAKDD2022. Submissions will be peer reviewed, single-blinded. Keynotes and invited talks: Several keynotes and invited talks by leading researchers in the area will be presented. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. We will use double-blind reviewing. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. We are in a conversation with some publishers once they confirm, we will announce accordingly. We collaborate with Saudi Aramco to use machine learning for simulating oil and water flows, . Proposals of technical talk (up to one-page abstract including short Bio of the main speaker). [Bests of ICDM]. In this workshop, we aim to address the trustworthy issues of clinical AI solutions. ACM Computing Surveys (CSUR), (impact factor: 10.28), accepted. Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. 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. Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. Submissions of technical papers can be up to 7 pages excluding references and appendices. Registration information will be mailed directly to all invited participants in December. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Yuyang Gao, Giorgio Ascoli, Liang Zhao. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. Event Prediction in the Big Data Era: A Systematic Survey. 10 (2014): e110206. 4 (2014): 185-195. of London). 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. Yuanqi du, George Mason University, USA; Jian Pei, Simon Fraser University, Canada; Charu Aggarwal, IBM Research AI, USA; Philip S. Yu, University of Illinois at Chicago, USA; Xuemin Lin, University of New South Wales, Australia; Jiebo Luo, University of Rochester, USA; Lingfei Wu, JD.Com Silicon Valley Research Center, USA; Yinglong Xia, Facebook AI, USA; Jiliang Tang, Michigan State University, USA; Peng Cui, Tsinghua University, China; William L. Hamilton, McGill University, Canada; Thomas Kipf, University of Amsterdam, Netherlands, Workshop URL:https://deep-learning-graphs.bitbucket.io/dlg-aaai22/. Yuyang Gao, Tong Sun, Guangji Bai, Siyi Gu, Sungsoo Hong, and Liang Zhao. Short or position papers of up to 4 pages are also welcome. Submissions may consist of up to 7 pages of technical content plus up to two additional pages solely for references. Researchers from related fields are invited to submit papers on the recent advances, resources, tools, and upcoming challenges for SDU. Attendance is open to all. The main interest of the proposed workshop is to look at a new perspective of system engineering where multiple disciplines such as AI and safety engineering are viewed as a larger whole, while considering ethical and legal issues, in order to build trustable intelligent autonomy. Guangji Bai and Liang Zhao. Furthermore, DNNs are data greedy in the context of supervised learning, and not well developed for limited label learning, for instance for semi-supervised learning, self-supervised learning, or unsupervised learning. ), 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). Optimal transport-based analysis of structured data, such as networks, meshes, sequences, and so on; The applications of optimal transport in molecule analysis, network analysis, natural language processing, computer vision, and bioinformatics. 1466-1469. Comparison or integration of self-supervised learning methods and other semi-supervised and transfer learning methods in speech and audio processing tasks. Neil T. Heffernan, Worcester Polytechnic Institute (Worcester, MA, USA), Andrew S. Lan, University of Massachusetts Amherst (Amherst, MA, USA), Anna N. Rafferty, Carleton College (Northfield, MN, USA), Adish Singla, Max Planck Institute for Software Systems (Saarbrucken, Germany). How can we develop solid technical visions and new paradigms about AI Safety? How can we characterize or evaluate AI systems according to their potential risks and vulnerabilities? of Graz), Cynthia Rudin (Duke Univ.) 625-634, New Orleans, US, Dec 2017. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. The papers may consist of up to seven pages of technical content plus up to two additional pages for references.
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