Yuyang Gao, Siyi Gu, Junji Jiang, Sungsoo Ray Hong, Dazhou Yu, and Liang Zhao. 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. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. We received 38 paper submissions and accepted 23 of them. Well also host a competition on adversarial ML along with this workshop. 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. 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. 14, 2022: The information of Keynote Speakers is available at, Apr. At least one author of each accepted submission must be present at the workshop. A primary reason for this is the inherent long-tailed nature of our world, and the need for algorithms to be trained with large amounts of data that includes as many rare events as possible. The workshop is being organized by application area or other, panels, invited speakers, interactive, small groups, discussions, presentations. Big data Journal (impact factor: 1.489), vo. We expect 50-65 people in the workshop. Liang Zhao's Homepage - Emory University Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. Pakdd 2022 Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph. Call for Papers Document Intelligence Workshop @ KDD 2022 Furthermore, leveraging AI to connect disparate social networks amongst teachers \\cite{karimi2020towards}, we may be able to provide greater resources for their planning, which have been shown to significantly affect students achievement. . Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. 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. By registering, you agree to receive emails from UdeM. KDD 2022. KDD 2022 Submissions are due by 12 November 2021. These complex demands have brought profound implications and an explosion of interest for research into the topic of this workshop, namely building practical AI with efficient and robust deep learning models. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. Large-scale Cost-aware Classification Using Feature Computational Dependency Graph. This proposed workshop will build upon successes and learnings from last years successful AI for Behavior Change workshop, and will focus on on advances in AI and ML that aim to (1) design and target optimal interventions; (2) explore bias and equity in the context of decision-making and (3) exploit datasets in domains spanning mobile health, social media use, electronic health records, college attendance records, fitness apps, etc. The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada AAAI is pleased to present the AAAI-22 Workshop Program. 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/. Contrast Pattern Mining in Paired Multivariate Time Series of Controlled Driving Behavior Experiment. Onn Shehory, Bar Ilan University (onn.shehory@biu.ac.il), Eitan Farchi, IBM Research Haifa (farchi@il.ibm.com), Guy Barash, Western Digital (Guy.Barash@wdc.com), Supplemental workshop site:https://sites.google.com/view/edsmls-2022/home. SIGMOD 2022 adheres to the ACM Policy Against Harassment. This cookie is set by GDPR Cookie Consent plugin. The goal of this workshop is to focus on creating and refining AI-based approaches that (1) process personalized data, (2) help patients (and families) participate in the care process, (3) improve patient participation, (4) help physicians utilize this participation to provide high quality and efficient personalized care, and (5) connect patients with information beyond that available within their care setting. Some examples of the success of information theory in causal inference are: the use of directed information, minimum entropy couplings and common entropy for bivariate causal discovery; the use of the information bottleneck principle with applications in the generalization of machine learning models; analyzing causal structures of deep neural networks with information theory; among others. Merge remote-tracking branch 'origin/master', 2. The accepted papers will be allocated either a contributed talk or a poster presentation. Characterization of fundamental limits of causal quantities using information theory. Knowledge Discovery and Data Mining. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. In other words, many existing FL solutions are still exposed to various security and privacy threats. Consequently, standard notions of software quality and reliability such as deterministic functional correctness, black box testing, code coverage, and traditional software debugging become practically irrelevant for ML systems. [Best Paper Candidate]. As deep learning problems become increasingly complex, network sizes must increase and other architectural decisions become critical to success. Attendance is open to all prior registration to the workshop/conference. 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. 76, pp. December, 12-16, 2022. Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu. The following paper categories are welcome: Submission site:https://sites.google.com/view/eaai-ws-2022/call, Silvia Tulli (Dept. This is a 1-day workshop involving talks by pioneer researchers from respective areas, poster presentations, and short talks of accepted papers. a fantastic tutorial on SIGKDD'09 by Prof. Eamonn Keogh (UC Riverside). Jos Miguel Hernndez-Lobato, University of CambridgeProf. By the end of this century, the earths population is projected to increase by 45% with available arable land decreasing by 20% coupled with changes in what crops these arable lands can best support; this creates the urgent need to enhance agricultural productivity by 70% before 2050. This workshop on Trustworthy Autonomous Systems Engineering (TRASE) offers an opportunity to highlight state of the art research in trustworthy autonomous systems, as well as provide a vision for future foundational and applied advances in this critical area at the intersection of AI and Cyber-Physical Systems. CFP - EasyChair Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang. Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. Comparison or integration of self-supervised learning methods and other semi-supervised and transfer learning methods in speech and audio processing tasks. We will accept both original papers up to 8 pages in length (including references) as well as position papers and papers covering work in progress up to 4 pages in length (not including references).Submission will be through Easychair at the AAAI-22 Workshop AI4DO submission site, Professor Bistra Dilkina (dilkina@usc.edu), USC and Dr. Segev Wasserkrug, (segevw@il.ibm.com), IBM Research, Prof. Andrea Lodi (andrea.lodi@cornell.edu), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (dharmash@us.ibm.com), IBM Research. We encourage long papers, short papers and demo papers. This topic encompasses forms of Neural Architecture Search (NAS) in which the performance properties of each architecture, after some training, are used to guide the selection of the next architecture to be tried. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). 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. RLG is a full-day workshop. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. Web applications along with text processing programs are increasingly being used to harness online data and information to discover meaningful patterns identifying emerging health threats. Submission instructions will be available at the workshop web page. Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng and Liang Zhao. 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. These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 24.31), accepted. Such advances would enrich the range of applicability of semi-autonomous systems to real-world tasks, most of which involve cooperation with one or more human partners. Guangji Bai, Chen Ling, Liang Zhao. It is difficult to expose false claims before they create a lot of damage. The workshop is organized by paper presentations.The length of the workshop: 1-day, 6-8 pages for full papers2-4 for poster/short/position papers, Submission URL:https://easychair.org/conferences/?conf=aaai-2022-workshop, Wenzhong Guo (Fuzhou University, fzugwz@163.com), Chin-Chen Chang (Feng Chia University, alan3c@gmail.com), Chi-Hua Chen (Fuzhou University, chihua0826@gmail.com), Haishuai Wang (Fairfield University & Harvard University, hwang@fairfield.edu), Feng-Jang Hwang (University of Technology Sydney), Cheng Shi (Xian University of Technology), Ching-Chun Chang (National Institute of Informatics, Japan). Cleansing and image enhancement techniques for scanned documents. Checklist for Revising a SIGKDD Data Mining Paper: However, you may visit "Cookie Settings" to provide a controlled consent. Mingxuan Ju, Wei Song, Shiyu Sun, Yanfang Ye, Yujie Fan, Shifu Hou, Kenneth Loparo, and Liang Zhao. The aim of the hack-a-thon is not only to foster innovation and potentially provide answers to outstanding research problems, but rather to engage the community and create new collaborations. 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. Deadlines are shown in America/Los_Angeles time. [slides] By clicking Accept All, you consent to the use of ALL the cookies. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), regular paper (acceptance rate: 8.9%), Singapore, Dec 2018, accepted. The extraction, representation, and sharing of health data, patient preference elicitation, personalization of generic therapy plans, adaptation to care environments and available health expertise, and making medical information accessible to patients are some of the relevant problems in need of AI-based solutions. The workshop will focus on both the theoretical and practical challenges related to the design of privacy-preserving AI systems and algorithms and will have strong multidisciplinary components, including soliciting contributions about policy, legal issues, and societal impact of privacy in AI. KDD 2022 Reveals Schedule of Data Mining and Knowledge Discovery Papers However, we will also accept anonymous submissions. 1059-1072, May 1 2017. Liang Zhao, Feng Chen, Jing Dai, Ting Hua, Chang-Tien Lu, and Naren Ramakrishnan. First, large data sources, both conventionally used in social sciences (EHRs, health claims, credit card use, college attendance records) and unconventional (social networks, fitness apps), are now available, and are increasingly used to personalize interventions. San Francisco, USA . OARS-KDD2022: KDD 2022 Workshop on Online and Adaptive Recommender Systems Washington DC, DC, United States, August 15, 2022 Topics: data science artificial intelligence recommender system recommendation KDD 2022 Workshop on Online and Adaptive Recommender Systems (OARS) Call For Papers ================== Submission URL:https://easychair.org/conferences/?conf=rl4edaaai22. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. Hence, this workshop will focus on introducing research progress on applying AI to education and discussing recent advances of handling challenges encountered in AI educational practice. Please refer tohttps://rl4ed.org/aaai2022/index.htmlfor additional information. We welcome full research papers, position papers, and extended abstracts. arXiv preprint arXiv:2207.09542 (2022). 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. The thematic sessions will be structured into short pitches and a common panel slot to discuss both individual paper contributions and shared topic issues. However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. iCal Outlook robotics Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, and Liang Zhao. The workshop aims at bridging formalisms for learning and reasoning such as neural and symbolic approaches, probabilistic programming, differentiable programming, Statistical Relation Learning and using non-differentiable optimization in deep models. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. https://doi.org/10.1007/s10707-019-00376-9. We invite paper submission with a focus that aligns with the goals of this workshop. ACM, 2013. Its capabilities have expanded from processing structured data (e.g. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), (acceptance rate: 16.8%), August 23-27, 2020, Virtual Event, CA, USA. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. Disease Contact Network. Algorithms for secure and privacy-aware machine learning for AI. Yuyang Gao, Giorgio Ascoli, Liang Zhao. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. Long papers (up to 6 pages + references) and extended abstracts (2 pages + references) are welcome, including resubmissions of already accepted papers, work-in-progress, and position papers. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . 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. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is Deadline: FSE 2023. Optimal transport theory, including statistical and geometric aspects; Gromov-Wasserstein distance and its variants; Bayesian inference for/with optimal transport; Gromovization of machine learning methods; Optimal transport-based generative modeling. Gabriel Pedroza (CEA LIST), Jos Hernndez-Orallo (Universitat Politcnica de Valncia, Spain), Xin Cynthia Chen (University of Hong Kong, China), Xiaowei Huang (University of Liverpool, UK), Huascar Espinoza (KDT JU, Belgium), Mauricio Castillo-Effen (Lockheed Martin, USA), Sen higeartaigh (University of Cambridge, UK), Richard Mallah (Future of Life Institute, USA), John McDermid (University of York, UK), Supplemental workshop site:http://safeaiw.org/. All papers must be submitted in PDF format, using the AAAI-22 author kit. A tag already exists with the provided branch name. STGEN: Deep Continuous-time Spatiotemporal Graph Generation. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning. The annual ACM SIGMOD/PODS Conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and . 4 (2014): 185-195. This workshop aims to provide a premier interdisciplinary forum for researchers in different communities to discuss the most recent trends, innovations, applications, and challenges of optimal transport and structured data modeling. The aim of this workshop is to focus on both original research and review articles on various disciplines of ITS applications, including particularly AI techniques for ITS time-series data analyses, ITS spatio-temporal data analyses, advanced traffic management systems, advanced traveler information systems, commercial vehicle operation systems, advanced vehicle control and safety systems, advanced public transportation services, advanced information management services, etc. All the workshop chairs, most of the Committees, and the authors of the accepted papers will attend the workshop also. We welcome submissions of long (max. Long talks (50 mins):Gabriel Peyr, (Mathematics, CNRS Senior Researcher);Yusu Wang, (Mathematics, Professor in CSE, UCSD);Caroline Uhler, (Statistics and CS, Associate Professor in EECS and IDSS, MIT); Short talks (25mins):Titouan Vayer, (Mathematics, Postdoctoral Researcher at ENS Lyon);Tam Le, (Computer Science, Research Scientist at RIKEN);Dixin Luo, (Computer Science, Assistant Professor in CS, Beijing Institute of Technology). in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. 205-214, San Francisco, California, Aug 2016. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. Published March 4, 2023 4:51 a.m. PST. It is important to learn how to use AI effectively in these areas in order to be able to motivate and help people to take actions that maximize their welfare. Table identification and extraction from business documents. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. What are the primary lessons learned from the model failures? KDD 2022 : Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. How to do good research, Get it published in SIGKDD and get it cited! BERT and GPT in NLP and SimCLR and BYOL in CV are famous examples in this direction. Fang Jin, Wei Wang, Liang Zhao, Edward Dougherty, Yang Cao, Chang-Tien Lu, and Naren Ramakrishnan. Ting Hua, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Association for the Advancement of Artificial Intelligence, The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada. Chen Ling, Carl Yang, and Liang Zhao. Balaraman Ravindran (Indian Institute of Technology Madras, India ravi@cse.iitm.ac.in), Balaraman Ravindran (Indian Institute of Technology Madras, India Primary contact (ravi@cse.iitm.ac.in), Kristian Kersting (TU Darmstadt, Germany, kersting@cs.tu-darmstadt.de), Sriraam Natarajan (Univ of Texas Dallas, USA, Sriraam.Natarajan@utdallas.edu), Ginestra Bianconi (Queen Mary University of London, UK, ginestra.bianconi@gmail.com), Philip S. Chodrow (University of California, Los Angeles, USA, phil@math.ucla.edu) Tarun Kumar (Indian Institute of Technology Madras, India, tkumar@cse.iitm.ac.in), Deepak Maurya (Purdue University, India, maurya@cse.iitm.ac.in), Shreya Goyal (Indian Institute of Technology Madras, India, Goyal.3@iitj.ac.in), Workshop URL:https://sites.google.com/view/gclr2022/.
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