"The EMBERS architecture for streaming predictive analytics." Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao. By registering, you agree to receive emails from UdeM. Robust Regression via Online Feature Selection under Adversarial Data Corruption. We will accept the extended abstracts of the relevant and recently published work too. Some of the key questions to be explored include: The workshop will take place in person and will span over one day. "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. This topic also encompasses techniques that augment or alter the network as the network is trained. Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. All submissions must be anonymous and conform to AAAI standards for double-blind review. In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. Online. 2022. The KDD 2022 program promises to be the most robust and diverse to date, with keynote presentations, industry-led sessions, workshops, and tutorials spanning a wide range of topics - from data-driven humanitarian mapping and applied data science in healthcare to the uses of artificial intelligence (AI) for climate mitigation and decision . Attendance is open to all; at least one author of each accepted paper must be virtually present at the workshop. Qiang Yang, Hong Kong University of Science and Technology/ WeBank, China, (qyang@cse.ust.hk ), Sin G. Teo, Institute for Infocomm Research, Singapore (teosg@i2r.a-star.edu.sg), Han Yu, Nanyang Technological University, Singapore (han.yu@ntu.edu.sg), Lixin Fan, WeBank, China (lixinfan@webank.com), Chao Jin, Institute for Infocomm Research, Singapore (jin_chao@i2r.a-star.edu.sg), Le Zhang, University of Electronic Science and Technology of China (zhangleuestc@gmail.com), Yang Liu, Tsinghua University, China (liuy03@air.tsinghua.edu.cn), Zengxiang Li, Digital Research Institute, ENN Group, China (lizengxiang@enn.cn), Workshop site:http://federated-learning.org/fl-aaai-2022/. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. Summer. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. Can AI achieve the same goal without much low-level supervision? In addition, authors can provide an optional one page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. The PAKDD is one of the longest established and leading international conferences in the areas of data mining and knowledge discovery. Realizing the vision of Document Intelligence remains a research challenge that requires a multi-disciplinary perspective spanning not only natural language processing and understanding, but also computer vision, layout understanding, knowledge representation and reasoning, data mining, knowledge discovery, information retrieval, and more all of which have been profoundly impacted and advanced by deep learning in the last few years. [Bests of ICDM], Zheng Zhang and Liang Zhao. 5, pp. We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette). ETA (expected time-of-arrival) prediction. ; (2) Deep Learning (DL) approaches that can exploit large datasets, particularly Graph Neural Networks (GNNs) and Deep Reinforcement Learning (DRL); (3) End-to-end learning methodologies that mend the gap between ML model training and downstream optimization problems that use ML predictions as inputs; (4) Datasets and benchmark libraries that enable ML approaches for a particular OR application or challenging combinatorial problems. 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. For instance, advanced driver assistance systems and autonomous cars have been developed based on AI techniques to perform forward collision warning, blind spot monitoring, lane departure warning systems, traffic sign recognition, traffic safety, infrastructure management and congestion, and so on. An Invertible Graph Diffusion Model for Source Localization. ACM, 2013. "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. [Best Paper Candidate]. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. Ferdinando Fioretto (Syracuse University), Aleksandra Korolova (University of Southern California), Pascal Van Hentenryck (Georgia Institute of Technology), Supplemental Workshop site:https://aaai-ppai22.github.io/. Funeral for Nadine Girault will take place Saturday | CTV News Bioinformatics (Impact Factor: 6.937), accepted, 2022. AI for infrastructure management and congestion. Big data Journal (impact factor: 1.489), vo. 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. We encourage all the teams who participated in the challenge to join the workshop. 105, no. 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. Algorithms and theories for explainable and interpretable AI models. The workshop attracted about 100 attendees. 3, pp. The submission website ishttps://cmt3.research.microsoft.com/PPAI2022. : Papers are submitted through the CMT portal for this workshop: Please select the track for your submission in Primary Subject Area and indicate if your submission is a full paper or an extended abstract in Secondary Subject Area. 1503-1512, Aug 2015. 11-13. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. We will end the workshop with a panel discussion by top researchers in the field. Feng Chen, Baojian Zhou, Adil Alim, Liang Zhao. KDD 2022 KDD . Accepted submissions will be notified latest by August 7th, 2022. Following this AAAI conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. Please refer to the KDD 2022 website for the policies of Conflict of Interest, Violations of Originality, and Dual Submission: A Best Paper Award will be presented to the best full paper as voted by the reviewers. 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. Submit to:https://openreview.net/group?id=AAAI.org/2022/Workshop/AdvML, Yinpeng Dong (dyp17@mails.tsinghua.edu.cn, 30 Shuangqing Road, Haidian District, Tsinghua University, Beijing, China, 100084, Phone: +86 18603303421), Yinpeng Dong (Tsinghua University, dyp17@mail.tsinghua.edu.cn), Tianyu Pang (Tsinghua University, pty17@mails.tsinghua.edu.cn), Xiao Yang (Tsinghua University, yangxiao19@mails.tsinghua.edu.cn), Eric Wong (MIT, wongeric@mit.edu), Zico Kolter (CMU, zkolter@cs.cmu.edu), Yuan He (Alibaba, heyuan.hy@alibaba-inc.com ). Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. DOI:https://doi.org/10.1145/3339823. All papers must be submitted in PDF format, using the AAAI-22 author kit. "Multi-Task Learning for Spatio-Temporal Event Forecasting." Although machine learning (ML) approaches have demonstrated impressive performance on various applications and made significant progress for AI, the potential vulnerabilities of ML models to malicious attacks (e.g., adversarial/poisoning attacks) have raised severe concerns in safety-critical applications. California, United Stes. Submissions will undergo double blind review. anomaly detection, and ensemble learning. IEEE Computer (impact factor: 3.564), vo. Explainable Agency captures the idea that AI systems will need to be trusted by human agents and, as autonomous agents themselves must be able to explain their decisions and the reasoning that produced their choices (Langley et al., 2017). Please email to Lingfei Wu: lwu@email.wm.edu for any query. The workshop page ishttps://sites.google.com/view/aaaiwfs2022, and it will include the most up-to-date information, including the exact schedule. Identification of key challenges and opportunities for future research. 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/. 1, 2022: Call For Paper: The Undergraduate Consortium at SIGKDD 2022 is available at, Mar. In addition to the keynote and presentations of accepted works, the workshop will include both a general discussion session on defining and addressing the key challenges in this area , and a lightning tutorial session that will include brief overviews and demos of relevant tools, including open source frameworks such as Ecole. Algorithms and theories for trustworthy AI models. The papers may consist of up to seven pages of technical content plus up to two additional pages for references. The program of the workshop will include invited talks, paper presentations and a panel discussion. 22, Issue 2. Unsupervised Deep Subgraph Anomaly Detection. The financial services industry relies heavily on AI and Machine Learning solutions across all business functions and services. Integration of Deep learning and Constraint programming. The consideration and experience of adversarial ML from industry and policy making. Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with human agents. We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. All papers must be submitted in PDF format using the AAAI-22 author kit. Please refer and submit through theLearning Network Architecture During Trainingworkshop website, which has more detailed information. Characterization of fundamental limits of causal quantities using information theory. Novel algorithms and theories to improve model robustness. AAAI-22 Workshop Program - AAAI Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. 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. Papers will be peer-reviewed and selected for oral and/or poster presentations at the workshop. Feature Constrained Multi-Task Learnings for Event Forecasting in Social Media." Papers more suited for a poster, rather than a presentation, would be invited for a poster session. 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. Natural language reasoning and inference. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). Two types of submissions will be considered: full papers (6-8 pages + references), and short papers (2-4 pages + references). We welcome full paper submissions (up to 8 pages, excluding references or supplementary materials). In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. a concise checklist by Prof. Eamonn Keogh (UC Riverside). 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.