689-698, Barcelona, Spain, Dec 2016. KDD 2022 : Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. An Invertible Graph Diffusion Model for Source Localization. The accelerated developments in the field of Artificial Intelligence (AI) hint at the need for considering Safety as a design principle rather than an option. with other vehicles via vehicular communication systems (e.g., dedicated short range communication (DSRC), vehicular ad hoc networks (VANETs), long term evolution (LTE), and 5G/6G mobile networks) for cooperation. In some programs, spots may be available after the deadlines. All extended abstracts and full papers are to be presented at the poster sessions. Online Flu Epidemiological Deep Modeling on Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. KDD 2023 August 06-10, 2023. The submission website ishttps://cmt3.research.microsoft.com/OTSDM2022. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International This topic also encompasses techniques that augment or alter the network as the network is trained. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. Modeling Health Stage Development of Patients with Dynamic Attributed Graphs in Online Health Communities. While original contributions are preferred, we also invite submissions of high-quality work that has recently been published in other venues or is concurrently submitted. 76, pp. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. Securing personal information, genomics, and intellectual property, Adversarial attacks and defenses on biomedical datasets, Detecting and preventing spread of misinformation, Usable security and privacy for digital health information, Phishing and other attacks using health information, Novel use of biometrics to enhance security, Machine learning (including RL) security and resiliency, Automation of data labeling and ML techniques, Operational and commercial applications of AI, Explanations of security decisions and vulnerability of explanations. Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia and Charu Aggarwal, "Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding", In the Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019), research track (acceptance rate: 14.2%), accepted, Alaska, USA, Aug 2019. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. Junxiang Wang, Liang Zhao, Yanfang Ye, and Yuji Zhang. Self-supervised learning (SSL) has shown great promise in problems involving natural language and vision modalities. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self, Rupinder Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Chris Kuhlman, Achla Marathe, Liang Zhao, Ting Hua, Feng Chen, et al.. "'Beating the news' with EMBERS:forecasting civil unrest using open source indicators." We welcome full research papers, position papers, and extended abstracts. We invite submission of papers describing innovative research and applications around the following topics. [Best Paper Award]. Continuous refinement of AI models using active/online learning. Information extraction from text and semi-structured documents. Wang, Shiyu, Yuanqi Du, Xiaojie Guo, Bo Pan, and Liang Zhao. 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. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. The workshop is being organized by application area or other, panels, invited speakers, interactive, small groups, discussions, presentations. A final tribute was paid on Saturday to former Coalition Avenir Qubec (CAQ) minister Nadine Girault, who died of lung cancer last month at age 63 . Algorithms and theories for trustworthy AI models. 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. How to do good research, Get it published in SIGKDD and get it cited! 4 pages) papers describing research at the intersection of AI and science/engineering domains including chemistry, physics, power systems, materials, catalysis, health sciences, computing systems design and optimization, epidemiology, agriculture, transportation, earth and environmental sciences, genomics and bioinformatics, civil and mechanical engineering etc. Novel approaches and works in progress are encouraged. Viliam Lisy (Czech Technical University in Prague, viliam.lisy@fel.cvut.cz), Noam Brown (Facebook AI Research, noambrown@fb.com), Martin Schmid (DeepMind, mschmid@google.com), Supplemental Workshop site:http://aaai-rlg.mlanctot.info/. Hyperparameters such as the number of layers, the number of nodes in each layer, the pattern of connectivity, and the presence and placement of elements such as memory cells, recurrent connections, and convolutional elements are all manually selected. a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette). Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. We are in a conversation with some publishers once they confirm, we will announce accordingly. DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. Check the CFP for details Deadline: ICDM 2020 . Accepted submissions will be notified latest by August 7th, 2022. 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. Workshop URL:https://rail.fzu.edu.cn/info/1014/1064.htm, Prof. Chi-Hua ChenEmail: chihua0826@gmail.comPostal address: No.2, Xueyuan Rd., Fuzhou, Fujian, ChinaTelephone: +86-18359183858. Liang Zhao, Junxiang Wang, and Xiaojie Guo. Registration information will be mailed directly to all invited participants in December. Would you like to mark this message as the new best answer? [Submission deadline extended, June 3] KDD 2022 Workshop on - INFORMS You can optionally export all deadlines to Google Calendar or .ics . Participants in the hack-a-thon will be asked to either register as a team or be randomly assigned to a team after registration. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. Big Data 2022 December 13-16, 2022. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. Key obstacles include lack of high-quality data, difficulty in embedding complex scientific and engineering knowledge in learning, and the need for high-dimensional design space exploration under constrained budgets. As Artificial Intelligence (AI) begins to impact our everyday lives, industry, government, and society with tangible consequences, it becomes increasingly important for a user to understand the reasons and models underlying an AI-enabled systems decisions and recommendations. While we are planning an in-person workshop to be held at AAAI-22, we aim to accommodate attendees who may not be able to travel to Vancouver by allowing participation via live virtual invited talks and virtual poster sessions. Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/ADAM, Aarti Singh (Carnegie Mellon University), Baskar Ganapathysubramanian (ISU), Chinmay Hegde (New York University; contact: chinmay.h@nyu.edu), Mark Fuge (University of Maryland), Olga Wodo (University of Buffalo), Payel Das (IBM), Soumalya Sarkar (Raytheon), Workshop website:https://adam-aaai2022.github.io/. 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. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. The acceptance decisions will take in account novelty, technical depth and quality, insightfulness, depth, elegance, practical or theoretical impact, reproducibility and presentation. In light of these issues, and the ever-increasing pervasiveness of AI in the real world, we seek to provide a focused venue for academic and industry researchers and practitioners to discuss research challenges and solutions associated with building AI systems under data scarcity and/or bias. At the AAAI-22 Workshop on Scientific Document Understanding (SDU@AAAI-22), we aim to gather insights into the recent advances and remaining challenges on scientific document understanding. Data Mining Conferences - GitHub The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, 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). simulation, evaluation and experimentation. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. The goal of this workshop is to connect researchers in self-supervision inside and outside the speech and audio fields to discuss cutting-edge technology, inspire ideas and collaborations, and drive the research frontier. in Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), research track (acceptance rate: 14.2%), accepted, Alaska, USA, Aug 2019. Complex systems are often characterized by several components that interact in multiple ways among each other. Liang Zhao, Ting Hua, Chang-Tien Lu, and Ing-Ray Chen. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Advances in AI technology, particularly perception and planning, have enabled unprecedented advances in autonomy, with autonomous systems playing an increasingly important role in day-to-day lives, with applications including IoT, drones, and autonomous vehicles. "EMBERS at 4 years:Experiences operating an Open Source Indicators Forecasting System." We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. Dynamic Tracking and Relative Ranking of Airport Threats from News and Social Media. This is especially the case for non-traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities with the sheer size and ever-increasing growth and change rate of their data. 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. Liyan Xu, Xuchao Zhang, Zong Bo, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho Choi. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. Yuyang Gao, Tong Sun, Guangji Bai, Siyi Gu, Sungsoo Hong, and Liang Zhao.