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). Neurocomputing (Impact Factor: 5.719), accepted. Three specific roles are part of this format: session chairs, presenters and paper discussants. 2085-2094, Aug 2016. It is difficult to expose false claims before they create a lot of damage. 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! Qingzhe Li, Liang Zhao, Jessica Lin and Yi-ching Lee. 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. The trained models are intended to assign scores to novel utterances, assessing whether they are possible or likely utterances in the training language. For general inquiries about AI2ASE, please write to the lead organizer aryan.deshwal@wsu.edu or jana.doppa@wsu.edu. [slides] It provides an international forum . anomaly detection, and ensemble learning. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. Submission Site:https://cmt3.research.microsoft.com/SAS2022, Abdelrahman Mohamed (Facebook, abdo@fb.com), Hung-yi Lee (NTU, hungyilee@ntu.edu.tw), Shinji Watanabe (CMU, shinjiw@ieee.org), Tara Sainath (Google, tsainath@google.com), Karen Livescu (TTIC, klivescu@ttic.edu), Shang-Wen Li (Facebook, shangwel@fb.com), Ewan Dunbar (University of Toronto, ewan.dunbar@utoronto.ca) Emmanuel Dupoux (EHESS/Facebook, dpx@fb.com), Workshop URL:https://aaai-sas-2022.github.io/. Can AI achieve the same goal without much low-level supervision? 2022. Participation of researchers from a wide variety of areas is encouraged, including Data Science, Machine Learning, Symbolic AI, Mathematical programming, Constraint Optimization, Reinforcement Learning, Dynamic control and Operations Research. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. Journal of Biomedical Semantics, (impact factor: 1.845), 2018, accepted. The 9th International Conference on Learning Representations (ICLR 2021), (acceptance rate: 28.7%), accepted. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. In recent years, various information theoretic principles have also been applied to different deep learning related AI applications in fruitful and unorthodox ways. The AAAI Workshop on Machine Learning for Operations Research (ML4OR) builds on the momentum that has been directed over the past 5 years, in both the OR and ML communities, towards establishing modern ML methods as a first-class citizen at all levels of the OR toolkit. The workshop also welcomes participants of SUPERB and Zero Speech challenge to submit their results. References will not count towards the page limit. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. All papers must be submitted in PDF format, using the AAAI-22 author kit. Submissions will go through a double-blind review process. What are the primary lessons learned from the model failures? IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 14.255), accepted. We welcome submissions of long (max. Multilingual document understanding methods and frameworks. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. In nearly all applications, reliability, safety, and security of such systems is a critical consideration. Deep learning and statistical methods for data mining. Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. [Best Poster Runner-Up Award]. Submission at:https://easychair.org/my/conference?conf=edsmls2022. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. The papers may consist of up to seven pages of technical content plus up to two additional pages for references. "Bridging the gap between spatial and spectral domains: A survey on graph neural networks." Deep Generative Model for Periodic Graphs. We send a public call and we assume the workshop will be of interest to many AAAI main conference audiences; we expect 50 participants. NOTE: Mandatory abstract deadline on Oct 13, 2022. Question answering on business documents. Shiyu Wang, Xiaojie Guo, Liang Zhao. Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong. Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang. The audience of this workshop will be researchers and students from a wide array of disciplines including, but not limited to, statistics, computer science, economics, public policy, psychology, management, and decision science, who work at the intersection of causal inference, machine learning, and behavior science. These challenges and issues call for robust artificial intelligence (AI) algorithms and systems to help. 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. 25, 2022: We have announced Call for Nominations: , Mar. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. algorithms applied to the above topics: deep learning, reinforcement learning, multi-armed bandits, causal inference, mathematical programming, and stochastic optimization. Modern surveillance systems employ tools and techniques from artificial intelligence and machine learning to monitor direct and indirect signals and indicators of disease activities for early, automatic detection of emerging outbreaks and other health-relevant patterns. Yuyang Gao, Tong Sun, Guangji Bai, Siyi Gu, Sungsoo Hong, and Liang Zhao. 3434-3440, Melbourne, Australia, Aug 2017. We will also organize 3 shared tasks in this workshop: punctuation restoration, domain adaptation for punctuation restoration, and chitchat detection. Using a social media account will simply make the application process easier: none of your activities on this site will be posted to your profile. KDD 2022 Reveals Schedule of Data Mining and Knowledge Discovery Papers Methods for learning network architecture during training, including Incrementally building neural networks during training, new performance benchmarks for the above. Paper Submission:November 12, 2021, 11:59 pm (anywhere on earth) Author Notification: December 3, 2021Full conference:February 22 March 1, 2022Workshop:February 28 March 1, 2022. Liang Zhao's Homepage - Emory University 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. Xiaojie Guo, Lingfei Wu, Liang Zhao. Papers that are under review at another conference or journal are acceptable for submission at this workshop, but we will not accept papers that have already been accepted or published at a venue with formal proceedings (including KDD 2022). In this 2nd instance of GCLR (Graphs and more Complex structures for Learning and Reasoning) workshop, we will focus on various complex structures along with inference and learning algorithms for these structures. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 20%=174/870), short paper, to appear, 2022. IEEE, 2014. California, United Stes. It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. IEEE Computer (impact factor: 3.564), vo. 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. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. Introduction: SIGKDD aims to provide the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining.SIGKDD will encourage: basic research in KDD (through annual research conferences, newsletter and other related activities . 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). in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), applied data science track, accepted (acceptance rate: 19.9%), pp. It will include multiple keynote speakers, invited talks, a panel discussion, and two poster sessions for the accepted papers. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). ACM RecSys 2022 will be held in Seattle, USA, from September 18 - 23, 2022. Atlanta, Georgia, USA . Zitao Liu (main contact) , TAL Education Group, liuzitao@tal.com, http://www.zitaoliu.com, Jiliang Tang (Michigan State University, tangjili@msu.edu, https://www.cse.msu.edu/~tangjili/), Lihan Zhao (TAL Education Group, zhaolihan@tal.com), and Xiao Zhai (TAL Education Group, zhaixiao@tal.com), Workshop URL:http://ai4ed.cc/workshops/aaai2022. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). SIGSPATIAL Special (invited paper), vo. Motif-guided Heterogeneous Graph Deep Generation. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. 507-516, Singapore, Nov 2017. 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. Oral presentations: 10 minute presentation for oral papers. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. Deep Generative Models for Spatial Networks. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. The review process will be single blind. DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. Template guidelines are here:https://www.acm.org/publications/proceedings-template. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. The scope of the workshop includes, but is not limited to, the following areas: We also invite participants to an interactive hack-a-thon. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. Amitava Das (Wipro AI Labs; amitava.santu@gmail.com), Workshop Chairs: Amitava Das (Wipro AI Labs) [India], Amit Sheth (University of South Carolina) [USA], Tanmoy Chakraborty (IIIT Delhi) [India], Asif Ekbal (IIT Patna) [India], Chaitanya Ahuja (CMU) [USA], Parth Patwa (UCLA) [USA], Parul Chopra (CMU) [USA], Amrit Bhaskar (ASU) [USA], Nethra Gunti (IIIT Sri City) [USA], Sathyanarayanan R. (IIIT Sri City) [India], Shreyash Mishra (IIIT Sri City) [India], S. Suryavardan (IIIT Sri City) [India], Vishal Pallagani (University of South Carolina), Supplemental workshop site:https://aiisc.ai/defactify/. Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. We solicit papers describing significant and innovative research and applications to the field of job marketplaces. Interpretable Molecular Graph Generation via Monotonic Constraints. The workshop is being organized by application area or other, panels, invited speakers, interactive, small groups, discussions, presentations. Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad,.
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