in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), short paper (acceptance rate: 19.9%), Singapore, Dec 2018, accepted. 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). It will include multiple keynote speakers, invited talks, a panel discussion, and two poster sessions for the accepted papers. Keynotes and invited talks: Several keynotes and invited talks by leading researchers in the area will be presented. 9, no. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), (Acceptance Rate: 26%), accepted. RES: A Robust Framework for Guiding Visual Explanation. In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. Aug 11, 2022: Get early access for registration at L Street Bridge, Washington DC Convention Center, from 4-6 pm, Saturday, August 13. We welcome the submissions in the following two formats: The submissions should adhere to theAAAI paper guidelines. ASPLOS 2023 will be moving to three submission deadlines. Hierarchical Incomplete Multisource Feature Learning for Spatiotemporal Event Forecasting. in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), research track (acceptance rate: 18.2%), San Francisco, California, pp. In some programs, spots may be available after the deadlines. Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu. "How events unfold: spatiotemporal mining in social media." The 19th International Conference on Data Mining (ICDM 2019), long paper, (acceptance rate: 9.08%), Beijing, China. This workshop aims to bring together FL researchers and practitioners to address the additional security and privacy threats and challenges in FL to make its mass adoption and widespread acceptance in the community. 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. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. The papers have to be submitted through EasyChair. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. The objective of this workshop is to discuss the winning submissions of the Submissions to the Amazon KDD Cup 2022 issingle-blind (author names and affiliations should be listed). 2022. Outcomes include outlining the main research challenges in this area, potential future directions, and cross-pollination between AI researchers and domain experts in agriculture and food systems. There were two workshops on similar topics hosted at ICML 2020 and NeurIPS 2020, and both workshops observed positive feedback and overwhelming participation. Interpretable Molecular Graph Generation via Monotonic Constraints. Babies learn their first language through listening, talking, and interacting with adults. A Report on the First Workshop on Document Intelligence (DI) at NeurIPS 2019. [Bests of ICDM], Zheng Zhang and Liang Zhao. Aug 11, 2022: Get early access for registration at L Street Bridge, Washington DC Convention Center, from 4-6 pm, Saturday, August 13. For example, AI tools are built to ease the workload for teachers. All these changes require novel solutions, and the AI community is well-positioned to provide both theoretical- and application-based methods and frameworks. 639-648, Nov 2015. Each paper will be reviewed by three reviewers in double-blind. Graph Neural Networks: Foundations, Frontiers, and Applications. There is a need for the research community to develop novel solutions for these practical issues. Disease Contact Network. Liang Zhao, Feng Chen, and Yanfang Ye. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Transfer learning methods for business document reading and understanding. Published March 4, 2023 4:51 a.m. PST. 2020. Proceedings of the ACM on Human-Computer Interaction (CSCW 2022), to appear, 2022. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. The main objective of the workshop is to bring researchers together to discuss ideas, preliminary results, and ongoing research in the field of reinforcement in games. The 9th International Conference on Learning Representations (ICLR 2021), (acceptance rate: 28.7%), accepted. Check the CFP for details Deadline: ICDM 2020 . 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. of London). Novel ML-accelerated optimization for conceptual/detailed system design. Junxiang Wang, Junji Jiang, Liang Zhao. The research contributions may discuss technical challenges of reading and interpreting business documents and present research results. 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/. How can we develop solid technical visions and new paradigms about AI Safety? Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. Specific topics of interest for the workshop include (but are not limited to) foundational and translational AI activities related to: The workshop will be a one day meeting comprising invited talks from researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work. IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 14.255), accepted. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. Supplemental Workshop site:https://rl4ed.org/aaai2022/index.html. KDD 2022. Integration of probabilistic inference in training deep models. AI is now shaping the way businesses, governments, and educational institutions do things and is making its way into classrooms, schools and districts across many countries. The cookie is used to store the user consent for the cookies in the category "Analytics". Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. Yuyang Gao, Tanmoy Chowdhury (co-first author), Lingfei Wu, Liang Zhao. In recent years, various information theoretic principles have also been applied to different deep learning related AI applications in fruitful and unorthodox ways. The workshop will be organized as a full day meeting. 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. Detailed information could be found on the website of the workshop. 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. Topics include, but our not limited to: learning optimization models from data, constraint and objective learning, AutoAI, especially if combined with decision optimization models or environments, AutoRL, incorporating the inaccuracy of the automatically learnt models in the decision making process, and using machine learning to efficiently solve combinatorial optimization models. Merge remote-tracking branch 'origin/master', 2. Kyoto . November 11-17, 2023. IEEE, 2014. 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. Continuous refinement of AI models using active/online learning. DI-2022 accepted papers will not be archived in the main KDD 2022 proceedings. Bioinformatics (Impact Factor: 6.937), accepted, 2022. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". If these formalities are not completed in time, you will have to file a new application at a later date. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Apr 11-14, 2022. This cookie is set by GDPR Cookie Consent plugin. It further combines academia and industry in a quest for well-founded practical solutions. Universit de MontralOffice of Admissions and RecruitmentC. Deep Graph Translation. It is one of the key bottlenecks for financial services companies to improve their operating productivity. Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market. fact-checking. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. Hence, there is a need for research and practical solutions to ML security problems.With these in mind, this workshop solicits original contributions addressing problems and solutions related to dependability, quality assurance and security of ML systems. Scott E. Fahlman, School of Computer Science, Carnegie Mellon University (sef@cs.cmu.edu), Edouard Oyallon, Sorbonne Universit LIP6 (Edouard.oyallon@lip6.fr), Dean Alderucci, School of Computer Science, Carnegie Mellon University, (dalderuc@cs.cmu.edu). At least one author of each accepted submission must present the paper at the workshop. In Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. sup-port vector machine (SVM), decision tree, random forest, etc.) To facilitate KDD related research, we create this repository with: *ICDM has two tracks (regular paper track and short paper track), but the exact statistic is not released, e.g., the split between these two tracks. Nonetheless, human-centric problems (such as activity recognition, pose estimation, affective computing, BCI, health analytics, and others) rely on information modalities with specific spatiotemporal properties. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. "A Topic-focused Trust Model for Twitter." The trustworthy issues of clinical AI methods were not discussed. One recommended setting for Latex file is:\documentclass[sigconf, review]{acmart}. : The fundamental mechanism of an online marketplace is to match supply and demand to generate transactions, with objectives considering service quality, participants experience, financial and operational efficiency. Microsoft's Conference Management Toolkit is a hosted academic conference management system. "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. It is difficult to expose false claims before they create a lot of damage. For previous workshops held physically, each workshop attracts around 150~300 participants. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. "Controllable Data Generation by Deep Learning: A Review." 1799-1808. 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. Deep Learning models are at the core of research in Artificial Intelligence research today. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. Natural language reasoning and inference. Authors of accepted papers will be invited to participate. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. KDD 2022 : 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Conference Series : Knowledge Discovery and Data Mining Link: https://kdd.org/kdd2022/ Call For Papers [Empty] Related Resources KDD 2023 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING IEEE Computer (impact factor: 3.564), vo. Submissions will undergo double blind review. Liming Zhang, Dieter Pfoser, Liang Zhao. Liang Zhao. 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. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. Jan 13, 2022: Notification. Yuyang Gao, Siyi Gu, Junji Jiang, Sungsoo Ray Hong, Dazhou Yu, and Liang Zhao. Extended abstracts should not exceed 2 pages, excluding references. Submissions that do not meet the formatting requirements will be rejected without review. Submission Guidelines It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. "Misinformation Propagation in the Age of Twitter." 4498-4505, New Orleans, US, Feb 2018. 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. NOTE: Mandatory abstract deadline: 2022-08-08 Deadline: AAAI 157. 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 ================== Knowledge Discovery and Data Mining. CFP - EasyChair Deadlines are shown in America/Los_Angeles time. Attendance is virtual and open to all. "GA-based principal component selection for production performance estimation in mineral processing." At least one author of each accepted submission must register and present their paper at the workshop. We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. "EMBERS at 4 years:Experiences operating an Open Source Indicators Forecasting System." The topics for AIBSD 2022 include, but are not limited to: This one-day workshop will include invited talks from keynote speakers, and oral/spotlight presentations of the accepted papers. . 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/. RAISAs systems-level perspective will be emphasized via three main thrusts: AI threat modeling, AI system robustness, explainable AI, system lifecycle attacks, system verification and validation, robustness benchmarks and standards, robustness to black-box and white-box adversarial attacks, defenses against training, operational and inversion attacks, AI system confidentiality, integrity, and availability, AI system fairness and bias. ACM, 2013. Interpretable Deep Graph Generation with Node-edge Codisentanglement. Submissions will go through a double-blind review process. Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, Bill Wuest, Amarda Shehu, Liang Zhao. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2014), industrial track, pp. We will end the workshop with a panel discussion by top researchers in the field. text, images, and videos). The 48th International Conference on Parallel Processing (ICPP 2019), (acceptance rate: 20%), accepted, Kyoto, Japan. Our preliminary plan for the schedule is as following , DEFACTIFY@AAAI-22 Program [tentative]9:00AM-9:15AMInaugurationA brief summary of the shared tasks number of participants, best results, Session 1 multimodal fact checkingWorkshop papers 9:30AM 10:30AM, 11:00AM 12:00pmInvited talk 1 Prof. Rada Mihalcea, University of Michigan, Session 2 Best 4/5 papers from FACTIFY & MEMOTION shared taskWorkshop papers 1:00PM 2:00PM, 2:00PM 3:30PMInvited talk 2 Prof. LOUIS-PHILIPPE MORENCY, CMU, Session 2 multimodal hate speechWorkshop papers 4:00PM 5:00PM. 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. Accepted papers will not be archived, and we explicitly allow papers that are concurrently submitted to, currently under review at, or recently accepted in other conferences / venues. What are the primary lessons learned from the model failures? have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). Modern interface, high scalability, extensive features and outstanding support are the signatures of Microsoft CMT. In recent years, machine learning techniques (e.g. "A Uniform Representation for Trajectory Learning Tasks", 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2017), short paper, DOI=10.1145/3139958.3140017, Redondo Beach, CA, USA, Nov 2017. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. We solicit papers describing significant and innovative research and applications to the field of job marketplaces. Finally, there is an increasing interest in AI in moving beyond traditional supervised learning approaches towards learning causal models, which can support the identification of targeted behavioral interventions. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond. 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). Two types of submissions will be considered: full papers (6-8 pages + references), and short papers (2-4 pages + references). PDF suitable for ArXiv repository (4 to 8 pages). Call for Papers Document Intelligence Workshop @ KDD 2022 3, pp. This website uses cookies to improve your experience while you navigate through the website. 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. Workshop registration is available to AAAI-22 technical registrants at a discounted rate, or separately to workshop only registrants. Neurocomputing (Impact Factor: 5.719), accepted. All submissions will be peer-reviewed. 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 cookies ensure basic functionalities and security features of the website, anonymously. 2022. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. CoRL 2023 97 days 17h 29m 15s November 06-09, 2023. And considering robustness, input data with noises frequently occur in open-world scenarios, which presents critical challenges for the building of robust AI systems in practice. 2022. Submitting a short or long paper to VDS will give authors a chance to present at VDS events at both ACM KDD 2022(hybrid) and IEEE VIS 2022( hybrid). 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. The adversarial ML could also result in potential data privacy and ethical issues when deploying ML techniques in real-world applications. Topics of interest in the biomedical space include: Topics of general interest to cyber-security include: Submission site:https://easychair.org/conferences/?conf=aics22, Tamara Broderick (MIT CSAIL, tamarab@mit.edu), James Holt (Laboratory for Physical Sciences, USA, holt@lps.umd.edu), Edward Raff (Booz Allen Hamilton, USA, Raff_Edward@bah.com), Ahmad Ridley (National Security Agency), Dennis Ross (MIT Lincoln Laboratory, USA, dennis.ross@ll.mit.edu), Arunesh Sinha (Singapore Management University, Singapore, aruneshs@smu.edu.sg), Diane Staheli (MIT Lincoln Laboratory, USA, diane.staheli@ll.mit.edu), William W. Streilein (MIT Lincoln Laboratory, USA, wws@ll.mit.edu), Milind Tambe (Harvard University, USA, milind_tambe@harvard.edu), Yevgeniy Vorobeychik (Washington University in Saint Louis, USA, eug.vorobey@gmail.com) Allan Wollaber (MIT Lincoln Laboratory, USA, Allan.Wollaber@ll.mit.edu), Supplemental workshop site:http://aics.site/.
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