[slides] All submissions will be peer-reviewed. Junxiang Wang, Liang Zhao, Yanfang Ye, and Yuji Zhang. The submissions must follow the formatting guidelines for AAAI-22. The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. Important Dates. November 11-17, 2023. For research track papers and applied data science track papers. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. Despite rapid recent progress, it has proven to be challenging for Artificial Intelligence (AI) algorithms to be integrated into real-world applications such as autonomous vehicles, industrial robotics, and healthcare. Jan 13, 2022: Notification. Natural language reasoning and inference. Government day with NSF, NIH, DARPA, NIST, and IARPA, Local industries in the DC Metro Area, including the Amazons second headquarter, New initiatives at KDD 2022: undergraduate research and poster session, Early career research day with postdoctoral scholars and assistant professors in a mentoring workshop and panel, Workshops and hands-on tutorials on emerging topics. We accept two types of submissions full research paper no longer than 8 pages (including references) and short/poster paper with 2-4 pages. The cookie is used to store the user consent for the cookies in the category "Performance". If the admission deadline for international applicants is past, we suggest that you choose another session to begin your studies. 1953-1970, Oct. 2017. Other submissions will be evaluated by a committee based on their novelty and insights. 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. Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2020), (acceptance rate: 20.6%), accepted. Keynotes and invited talks: Several keynotes and invited talks by leading researchers in the area will be presented. Aug 14-18. We also use third-party cookies that help us analyze and understand how you use this website. TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints. Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu. 2020. 2022. Bioinformatics (Impact Factor: 6.937), accepted, 2022. Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market. "A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks", in Proceedings of the IEEE International Conference on Data Mining (ICDM 2017) , regular paper; (acceptance rate: 9.25%), pp. Topics of interest include, but are not limited to: Paper submissions will be in two formats: full paper (8 pages) and position paper (4 pages): The submission website ishttps://easychair.org/conferences/?conf=trase2022. Submissions will go through a double-blind review process. Submissions will undergo double blind review. ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices. The adversarial ML could also result in potential data privacy and ethical issues when deploying ML techniques in real-world applications. Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. All the submissions should be anonymous. Methods for learning network architecture during training, including Incrementally building neural networks during training, new performance benchmarks for the above. Short or position papers of up to 4 pages are also welcome. Notable examples include the information bottleneck (IB) approach on the explanation of the generalization behavior of DNNs and the information maximization principle in visual representation learning. Because of the time needed to complete the formalities for entering Canada and Quebec, the admission period for international applicants ends several weeks before the session begins. In Proceedings of the 20th International Conference on Data Mining (ICDM 2020), (acceptance rate: 9.8%), November 17-20, 2020, Virtual Event, Sorrento, Italy, 10 pages. Submission site:https://easychair.org/conferences/?conf=kdf22, Chair:Xiaomo Liu (J.P. Morgan Chase AI Research, xiaomo.liu@jpmchase.com), Zhiqiang Ma (J.P. Morgan Chase AI Research), Armineh Nourbakhsh (J.P. Morgan Chase AI Research), Sameena Shah (J.P. Morgan Chase AI Research), Gerard de Melo (Hasso Plattner Institute), Le Song (Mohamed bin Zayed University of Artificial Intelligence), Workshop URL:https://aaai-kdf.github.io/kdf2022/. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Each accepted paper presentation will be allocated between 15 and 20 minutes. Hua, Ting, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Xiaojie Guo, Yuanqi Du, Liang Zhao. Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting.Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), (acceptance rate: 16.2%), Hawaii, USA, Feb 2019, accepted. However, FL also faces multiple challenges that may potentially limit its applications in real-world use scenarios. Feng Chen, Baojian Zhou, Adil Alim, Liang Zhao. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. Applications of causal inference and discovery in machine learning/deep learning motivated by information-theoretic approaches (e.g. These cookies will be stored in your browser only with your consent. 1923-1935, 1 Oct. 2020, doi: 10.1109/TKDE.2019.2912187. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), (Acceptance Rate: 26%), accepted. Checklist for Revising a SIGKDD Data Mining Paper, How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering, https://researcher.watson.ibm.com/researcher/view_group.php?id=144, IEEE International Conference on Big Data (, AAAI Conference on Artificial Intelligence (, IEEE International Conference on Data Engineering (, SIAM International Conference on Data Mining (, Pacific-Asia Conference on Knowledge Discovery and Data Mining (, ACM SIGKDD International Conference on Knowledge discovery and data mining (, European Conference on Machine learning and knowledge discovery in databases (, ACM International Conference on Information and Knowledge Management (, IEEE International Conference on Data Mining (, ACM International Conference on Web Search and Data Mining (, 18.4% (181/983, research track), 22.5% (112/497, applied data science track), 59.1% (107/181, research track), 35.7% (40/112, applied data science track), 17.4% (130/748, research track), 22.0% (86/390, applied data science track), 49.2% (64/130, research track), 41.9% (36/86, applied data science track), 18.1% (142/784, research track), 19.9% (66/331, applied data science track), 49.3% (70/142, research track), 60.1% (40/66, applied data science track), 18.5% (194/1046, overall), 9.1% (95/?, regular paper), ?% (99/?, short paper), 19.8% (188/948, overall), 8.9% (84/?, regular paper), ?% (104/?, short paper), 19.9% (155/778, overall), 9.3% (72/?, regular paper), ?% (83/?, short paper), 19.6% (178/904, overall), 8.6% (78/?, regular paper), ?% (100/?, short paper), 19.6% (202/1031, long paper), 22.7% (107/471, short paper), 21.8% (38/174m applied research), 17% (147/826, long paper), 23% (96/413, short paper), 25% (demo), 34% (industry paper), Short papers are presented at poster sessions, 20% (171/855, long paper), 28% (119/419, short paper), 38% (30/80, demo paper), 23% (160/701, long paper), 24% (55/234, short paper), 54 extended short papers (6 pages), 26% (94/354, research track), 26% (37/143, applied ds track), 15% (23/151, journal track), 27.8% (164/592, overall), 9.8% (58/592, long presentation), 18.1% (107/592, regular), 28.2% (129/458, overall), 9.8% (45/458, long presentation), 18.3% (84/458, regular), 29.6% (91/307, overall), 12.7% (39/307, long presentation), 16.9% (52/307, regular), 40.4% (34/84, long presentation), 59.5% (50/84, short presentation)^, 16.3% (84/514 in which 3 papers are withdrawn/rejected after the acceptance), 28.4% (23/81, long presentation), 71.6% (58/81, short presentation)^, 30% (24/80, long presentation), 70% (56/80, short presentation)^, 29.8% (20/67, long presentation), 70.2% (47/67, short presentation)^, 53.8% (21/39, long presentation), 46.2% (18/39, short presentation)^. IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 24.31), accepted. DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. World Wide Web Conference (WWW 2018), (acceptance rate: 14.8%), Lyon, FR, Apr 2018, accepted. All extended abstracts and full papers are to be presented at the poster sessions. "Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System." Registration information will be mailed directly to all invited participants in December. Oct 14, 2021: Abstract Deadline. applications: ridesharing, online retail, food delivery, house rental, real estate, and more. . We invite participants to submit papers by the 12th of November, based on but not limited to, the following topics: RL in various formalisms: one-shot games, turn-based, and Markov games, partially-observable games, continuous games, cooperative games; deep RL in games; combining search and RL in games; inverse RL in games; foundations, theory, and game-theoretic algorithms for RL; opponent modeling; analyses of learning dynamics in games; evolutionary methods for RL in games; RL in games without the rules; search and planning; and online learning in games. Washington DC, USA. This topic also encompasses techniques that augment or alter the network as the network is trained. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Jiabin Wang, and Qi Xiong. Alan Yuille (Professor, Johns Hopkins University); Hao Su (Assistant Professor, UC San Diego); Rongrong Ji (Professor, Xiamen University); Xianglong Liu (Professor, Beihang University); Jishen Zhao (Associate Professor, UC San Diego); Tom Goldstein (Associate Professor, University of Maryland); Cihang Xie (Assistant Professor, UC Santa Cruz); Yisen Wang (Assistant Professor, Peking University); Bohan Zhuang (Assistant Professor, Monash University), Haotong Qin (Beihang University), Yingwei Li (Johns Hopkins University), Ruihao Gong (SenseTime Research), Xinyun Chen (UC Berkeley), Aishan Liu (Beihang University), Xin Dong (Harvard University), Jindong Guo (University of Munich), Yuhang Li (Yale University), Yiming Li (Tsinghua University), Yifu Ding (Beihang University), Mingyuan Zhang (Nanyang Technological University), Jiakai Wang (Beihang University), Jinyang Guo (University of Sydney), Renshuai Tao (Beihang University), Workshop site:https://practical-dl.github.io/. 3434-3440, Melbourne, Australia, Aug 2017. Each paper will be reviewed by three reviewers in double-blind. We are in a conversation with some publishers once they confirm, we will announce accordingly. How to do good research, Get it published in SIGKDD and get it cited! The workshop will focus on the application of AI to problems in cyber-security. 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. Meta-learning models from various existing task-specific AI models. Participants will be given access to publicly available datasets and will be asked to use tools from AI and ML to generate insight from the data. Proceedings of the IEEE (impact factor: 9.237), vol. References will not count towards the page limit. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021), (acceptance rate: 15.4%), accepted. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. In Proceedings of the 20th International Conference on Data Mining (ICDM 2020), (acceptance rate: 9.8%), November 17-20, 2020, Virtual Event, Sorrento, Italy, 10 pages. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. This date takes priority over those shown below and could be extended for some programs. [Bests of ICDM], Zheng Zhang and Liang Zhao. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Deep Graph Learning for Circuit Deobfuscation. a concise checklist by Prof. Eamonn Keogh (UC Riverside). Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. PDF suitable for ArXiv repository (4 to 8 pages). 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 . Previous healthcare-related workshops focus on how to develop AI methods to improve the accuracy and efficiency of clinical decision-making, including diagnosis, treatment, triage. Theoretical or empirical studies focusing on understanding why self-supervision methods work for speech and audio. Shiyu Wang, Xiaojie Guo, Liang Zhao. Submission URL:https://easychair.org/my/conference?conf=vtuaaai2022. Distant-supervision of heterogeneous multitask learning for social event forecasting with multilingual indicators. The workshop will focus on two thrusts: 1) Exploring how we can leverage recent advances in RL methods to improve state-of-the-art technology for ED; 2) Identifying unique challenges in ED that can help nurture technical innovations and next breakthroughs in RL. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. Papers should be up to 4 pages in length (excluding references) formatted using the AAAI template. "Robust Regression via Heuristic Hard Thresholding". 2020. All these changes require novel solutions, and the AI community is well-positioned to provide both theoretical- and application-based methods and frameworks. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. Published March 4, 2023 4:51 a.m. PST. Integration of Deep learning and Constraint programming. The research contributions may discuss technical challenges of reading and interpreting business documents and present research results. 2999-3006, New Orleans, US, Feb 2018. Research track papers reporting the results of ongoing or new research, which have not been published before. PLOS ONE (impact factor: 3.534), vo. Maria Malik, Hassan Ghasemzadeh, Tinoosh Mohsenin, Rosario Cammarota, Liang Zhao, Avesta Sasan, Houman Homayoun, Setareh Rafatirad. [Call for papers] KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, CFP: IJCAI 2021 Reinforcement Learning for Intelligent Transportation Systems Workshop, Second Workshop on Marketplace Innovation. Submission link:https://easychair.org/cfp/raisa-2022, William Streilein, MIT Lincoln Laboratory, 244 Wood St., Lexington, MA, 02420, (781) 981-7200, wws@ll.mit.edu, Olivia Brown (MIT Lincoln Laboratory, Olivia.Brown@ll.mit.edu), Rajmonda Caceres (MIT Lincoln Laboratory, Rajmonda.Caceres@ll.mit.edu), Tina Eliassi-Rad (Northeastern University, teliassirad@northeastern.edu), David Martinez (MIT Lincoln Laboratory, dmartinez@ll.mit.edu), Sanjeev Mohindra (MIT Lincoln Laboratory, smohindra@ll.mit.edu), Elham Tabassi (National Institute of Standards and Technology, elham.tabassi@nist.gov), Workshop URL:https://sites.google.com/view/raisa-2022/. The workshop plans to invite about 50-75 participants. The AAAI-22 workshop program includes 39 workshops covering a wide range of topics in artificial intelligence. ), responsible development of human-centric SSL (e.g., safety, limitations, societal impacts, and unintended consequences), ethical and legal implications of using SSL on human-centric data, implications of SSL on robustness and fairness, implications of SSL on privacy and security, interpretability and explainability of human-centric SSL frameworks, if your work broadly addresses the use of unlabeled human-centric data with unsupervised or semi-supervised learning, if your work focuses on architectures and frameworks for SSL for sensory data beyond CV and NLP (but not necessarily human-centric data). SIGMOD 2022 adheres to the ACM Policy Against Harassment. The submissions need to be anonymized. An increasing world population, coupled with finite arable land, changing diets, and the growing expense of agricultural inputs, is poised to stretch our agricultural systems to their limits. Accepted submissions will be notified latest by August 7th, 2022. The submitted contributions will be peer-reviewed by the Program Committee, and preference will be given to high-quality original and relevant work to the Document Intelligence topics. How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: We send a public call and we assume the workshop will be of interest to many AAAI main conference audiences; we expect 50 participants. KDD is the premier Data Science conference. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. 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. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. It leverages many emerging privacy-preserving technologies (SMC, Homomorphic Encryption, differential privacy, etc.) The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". Undergraduate (bachelor's, certificate, etc. 2022. Submissions should follow the AAAI-2022https://aaai.org/Conferences/AAAI-22/aaai22call/. The workshop will be organized as a full day meeting. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. The following paper categories are welcome: Submission site:https://sites.google.com/view/eaai-ws-2022/call, Silvia Tulli (Dept. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. Accepted papers are likely to be archived. And with particular focuses but not limited to these application domains: Our program consists of two sessions: academic session and industry session. 2022. The reproducibility papers include a clarification phase: Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, and Liang Zhao. RES: A Robust Framework for Guiding Visual Explanation. Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. The last few years have seen the rapid development of mathematical methods for modeling structured data coming from biology, chemistry, network science, natural language processing, and computer vision applications. Submissions can be original research contributions, or abstracts of papers previously submitted to top-tier venues, but not currently under review in other venues and not yet published. 2022. Fine tuning a neural network is very time consuming and far from optimal. 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. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. We invite the submission of papers with 4-6 pages. 1145/3394486.3403221. Even in cases where one is able to collect data, there are inherently many kinds of biases in this process, leading to biased models. Geoinformatica, (impact factor: 2.392), Volume 20, Issue 4, pp 765-795, Oct 2016. 963-971, Apr-May 2015. The theme of the hack-a-thon will be decided before submission is closed and will be focused around finding creative solutions to novel problems in health. Junxiang Wang, Fuxun Yu, Xiang Chen, and Liang Zhao. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. ML4OR will serve as an interdisciplinary forum for researchers in both fields to discuss technical issues at this interface and present ML approaches that apply to basic OR building blocks (e.g., integer programming solvers) or specific applications. In this workshop, we want to explore ways to bridge short-term with long-term issues, idealistic with pragmatic solutions, operational with policy issues, and industry with academia, to build, evaluate, deploy, operate and maintain AI-based systems that are demonstrably safe. KDD 2023 August 06-10, 2023. Please submit the papers and system reports toEasyChair, Thien Huu Nguyen (University of Oregon, thien@cs.uoregon.edu), Walter Chang (Adobe Research, wachang@adobe.com), Amir Pouran Ben Veyseh (University of Oregon, apouranb@uoregon.edu), Viet Dac Lai (University of Oregon, viet@uoregon.edu), Franck Dernoncourt (Adobe Research, franck.dernoncourt@adobe.com), Workshop URL:https://sites.google.com/view/sdu-aaai22/home. A 2-day workshop to share knowledge and research on five tracks of DSTC-10 and general related technical track. Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. Modern interface, high scalability, extensive features and outstanding support are the signatures of Microsoft CMT. Proposals of technical talk (up to one-page abstract including short Bio of the main speaker). Deep learning has achieved significant success for artificial intelligence (AI) in multiple fields. 4 pages), and position (max. Share. This workshop aims to discuss important topics about adversarial ML to deepen our understanding of ML models in adversarial environments and build reliable ML systems in the real world. The trustworthy issues of clinical AI methods were not discussed. Yuyang Gao, Giorgio Ascoli, Liang Zhao. The workshop will include several technical sessions, a virtual poster session where presenters can discuss their work, to further foster collaborations, multiple invited speakers covering crucial aspects for the practical deep learning in the wild, especially the efficient and robust deep learning, some tutorial talks, the challenge for efficient deep learning and solution presentations, and will conclude with a panel discussion.
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