Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. Amir A. Fanid, Monireh Dabaghchian, Ning Wang, Pu Wang, Liang Zhao, Kai Zeng. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. The automated processing of unstructured data to discover knowledge from complex financial documents requires a series of techniques such as linguistic processing, semantic analysis, and knowledge representation & reasoning. 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. Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, "Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation", ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 1.98), accepted, 2019. While most work on XAI has focused on opaque learned models, this workshop also highlights the need for interactive AI-enabled agents to explain their decisions and models. Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. GNES: Learning to Explain Graph Neural Networks. Social Media based Simulation Models for Understanding Disease Dynamics. The format is the standard double-column AAAI Proceedings Style. 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. Our intent is to facilitate new AI/ML advances for core engineering design, simulation, and manufacturing. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. 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. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. 9, no. We invite novel contributions following the AAAI-22 formatting guidelines, camera-ready style. All submissions will be peer-reviewed. Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. The discussion in the workshop can lead to implementing FL solutions that are more accurate, robust and interpretable, and gain the trust of the FL participants. Short or position papers of up to 4 pages are also welcome. For example, failures in IoT can result in infrastructure disruptions, and failures in autonomous cars can lead to congestion and crashes. AI Conference Deadlines 5 (2014): 1447-1459. Thank you for all your contributions, our, Paper submission deadline is now extended to. 625-634, New Orleans, US, Dec 2017. Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad,. Second, psychological experiments in laboratories and in the field, in partnership with technology companies (e.g., using apps), to measure behavioral outcomes are being increasingly used for informing intervention design. Computers & Electrical Engineering (impact factor: 2.189), vo. Chen Ling, Carl Yang, and Liang Zhao. The papers have to be submitted through EasyChair. Babies learn their first language through listening, talking, and interacting with adults. Yuyang Gao 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 2022 Reveals Schedule of Data Mining and Knowledge Discovery Papers These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. In addition, broad deployment of ML software in networked systems inevitably exposes ML software to attacks. 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/. Deep Multi-attributed Graph Translation with Node-Edge Co-evolution. Deep learning and statistical methods for data mining. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. The AAAI-22 workshop program includes 39 workshops covering a wide range of topics in artificial intelligence. The workshop welcomes the submission of work on, but not limited to, the following research directions. 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. While the research community is converging on robust solutions for individual AI models in specific scenarios, the problem of evaluating and assuring the robustness of an AI system across its entire life cycle is much more complex. 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! The robust development and assured deployment of AI systems: Participants will discuss how to leverage and update common software development paradigms, e.g., DevSecOps, to incorporate relevant aspects of system-level AI assurance. Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. 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. 1-11, Feb 2016. In addition, several invited speakers with distinguished professional background will give talks related the frontier topics of GNN. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. Yanfang Ye, Yiming Zhang, Yujie Fan, Chuan Shi and Liang Zhao. Additional information about formatting and style files is available here: : Full papers are limited to a total of 6 pages, including all content and references. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. The challenge requires participants to build competitive models for diverse downstream tasks with limited labeled data and trainable parameters, by reusing self-supervised pre-trained networks. a fantastic tutorial on SIGKDD'09 by Prof. Eamonn Keogh (UC Riverside). It does not store any personal data. DI-2022 accepted papers will not be archived in the main KDD 2022 proceedings. Short or position papers of up to 4 pages are also welcome. a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette). Submission instructions will be available at the workshop web page. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. Please note that foreign students must allow for 3 to 6 months to complete all the formalities required to study in Canada. Encore track papers that have been recently published, or accepted for publication in a conference or journal. The paper submissions must be in pdf format and use the AAAI official templates. 8 pages), short (max. Recent years have witnessed growing efforts from the AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in education. Applications of causal inference and discovery in machine learning/deep learning motivated by information-theoretic approaches (e.g. We consider submissions that havent been published in any peer-reviewed venue (except those under review). Attendance is open to all prior registration to the workshop/conference. [Bests of ICDM]. Yuyang Gao, Giorgio Ascoli, Liang Zhao. Qingzhe Li, Jessica Lin, Liang Zhao and Huzefa Rangwala. Half day event featuring a panel, invited and keynote speakers and presentations selected through a CFP. Taking the pulse of COVID-19: a spatiotemporal perspective. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). At the same time, multimodal hate-speech detection is an important problem but has not received much attention. Submission site:https://cmt3.research.microsoft.com/DSTC102022, Koichiro Yoshino,Address: 2-2-2, Seika, Sohraku, Kyoto, 6190288, JapanAffiliation: RIKENPhone: +81-774-95-1360Email: koichiro.yoshino@riken.jp, Yun-Nung (Vivian) ChenAddress: No. 2022. The papers may consist of up to seven pages of technical content plus up to two additional pages for references. Pattern Recognition, (impact factor: 7.196),112 (2021): 107711. The workshop invites contribution to novel methods, innovations, applications, and broader implications of SSL for processing human-related data, including (but not limited to): In addition to the above, papers that consider the following are also invited: Manuscripts that fit only certain aspects of the workshop are also invited. "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. [materials][data]. [Best Paper Award Shortlist]. Liang Zhao, Feng Chen, Jing Dai, Ting Hua, Chang-Tien Lu, and Naren Ramakrishnan. Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. We are excited to announce our upcoming workshop at KDD 2022 | Washington DC, U.S.: Decision Intelligence and Analytics for Online Marketplaces - Jobs, Ridesharing, Retail, and Beyond. These cookies ensure basic functionalities and security features of the website, anonymously. KDD 2023 August 06-10, 2023. 19-25, 2016. Junxiang Wang, Liang Zhao, Yanfang Ye, and Yuji Zhang. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. Online . It is one of the key bottlenecks for financial services companies to improve their operating productivity. 2020. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). 639-648, Nov 2015. 2022. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. Research track papers reporting the results of ongoing or new research, which have not been published before. Three categories of contributions are sought: full-research papers up to 8 pages; short papers up to 4 pages; and posters and demos up to 2 pages. At least one author of each accepted submission must register and present the paper at the workshop. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. Benchmarks to reliably evaluate attacks/defenses and measure the real progress of the field. All papers must be submitted in PDF format using the AAAI-22 author kit. The workshop will be a one-day workshop, featuring speakers, panelists, and poster presenters from machine learning, biomedical informatics, natural language processing, statistics, behavior science. Template guidelines are here:https://www.acm.org/publications/proceedings-template. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. Furthermore, DNNs are data greedy in the context of supervised learning, and not well developed for limited label learning, for instance for semi-supervised learning, self-supervised learning, or unsupervised learning. Generative Deep Learning for Macromolecular Structure and Dynamics, Current Opinion in Structural Biology, (impact factor: 7.108), Section on Theory and Simulation/Computational Methods 67: 170-177, 2021 accepted. search, ranking, recommendation, and personalization. Integrated syntax and semantic approaches for document understanding. AI System Robustness: participants will consider techniques for detecting and mitigating vulnerabilities at each of the processing stages of an AI system, including: the input stage of sensing and measurement, the data conditioning stage, during training and application of machine learning algorithms, the human-machine teaming stage, and during operational use. 4498-4505, New Orleans, US, Feb 2018. Options include pruning a trained network or training many networks automatically. Deadline: FSE 2023. How can we characterize or evaluate AI systems according to their potential risks and vulnerabilities? It will include multiple keynote speakers, invited talks, a panel discussion, and two poster sessions for the accepted papers. The workshop organizers invite paper submissions on the following (and related) topics: This workshop will be a one-day workshop, featuring invited speakers, poster presentations, and short oral presentations of selected accepted papers. The topics of interest include but are not limited to: Theoretical and Computational Optimal Transport: Optimal Transport-Driven Machine Learning: Optimal Transport-Based Structured Data Modeling: The full-day workshop will start with two long talks and one short talk in the morning. Submissions will be accepted via the Easychair submission website. The main research questions and topics of interest include, but are not limited to: This will be a one day workshop, including four invited speakers, one panel session, a number of oral presentations of the accepted long papers and two poster sessions for all accepted papers including short and long. Winter. Junxiang Wang, Hongyi Li, Liang Zhao. "TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction", the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2019 (SIGSPATIAL 2019), long paper, (acceptance rate: 21.7%), Chicago, Illinois, USA, accepted. In decision-making domains as wide-ranging as medication adherence, vaccination uptakes, college enrollment, retirement savings, and energy consumption, behavioral interventions have been shown to encourage people towards making better choices. The workshop also welcomes participants of SUPERB and Zero Speech challenge to submit their results. Junxiang Wang, Yuyang Gao, Andreas Zufle, Jingyuan Yang, and Liang Zhao. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. 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. Videos have become an omnipresent source of knowledge: courses, presentations, conferences, documentaries, live streams, meeting recordings, vlogs. 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. Novel AI-based techniques to improve modeling of engineering systems. Data mining systems and platforms, and their efficiency, scalability, security and privacy. Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. Deadline: Fri Jun 09 2023 04:59:00 GMT-0700 Yahoo! These challenges are widely studied in enterprise networks, but there are many gaps in research and practice as well as novel problems in other domains. We invite submission of papers describing innovative research and applications around the following topics. Aryan Deshwal (Washington State University, aryan.deshwal@wsu.edu), Syrine Belakaria (Washington State University, syrine.belakaria@wsu.edu), Cory Simon (Oregon State University, cory.simon@oregonstate.edu), Jana Doppa (Washington State University, jana.doppa@wsu.edu), Yolanda Gil (University of Southern California, gil@isi.edu), Supplemental workshop site:https://ai-2-ase.github.io/. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Kaiqun Fu, Taoran Ji, Liang Zhao, and Chang-Tien Lu. You can optionally export all deadlines to Google Calendar or .ics . What safety engineering considerations are required to develop safe human-machine interaction? 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. The Conference. Pakdd 2022 AD Conference Deadlines 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. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. DeepGAR: Deep Graph Learning for Analogical Reasoning. IEEE Transactions on Knowledge and Data Engineerings (TKDE), (impact factor: 6.977), accepted. 25-50 attendees including invited speakers and accepted papers. Frontiers in Big Data, accepted, 2021. Interpretable Deep Graph Generation with Node-edge Codisentanglement. We also invite papers that have been published at other venues to spark discussions and foster new collaborations. SIGMOD 2022 adheres to the ACM Policy Against Harassment. Oral Paper (Top 5% among the accepted papers). Frontiers in Neurorobotics, (impact factor: 2.574), accepted. Self-supervised learning (SSL) has shown great promise in problems involving natural language and vision modalities. Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with human agents. New self-supervised proxy tasks or new approaches using self-supervised models in speech and audio processing. Please keep your paper format according to AAAI Formatting Instructions (two-column format). in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. Xiaosheng Li, Jessica Lin, and Liang Zhao. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. "Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling." A message will appear on your application form if there is a risk that the time required to process the application and to send the answer, in addition to the time you will need to acquire study permits, will be too long for you to arrive for the beginning of the session. 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. Springer, Singapore. These choices can only be analyzed holistically if the technological and ethical perspectives are integrated into the engineering problem, while considering both the theoretical and practical challenges of AI safety. Dynamic Tracking and Relative Ranking of Airport Threats from News and Social Media. The scope of the workshop includes, but is not limited to, the following areas: We also invite participants to an interactive hack-a-thon. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. IEEE, 2014. ADMM for Efficient Deep Learning with Global Convergence. Oilers Outperform Division Rivals at 2023 Trade Deadline Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Jiabin Wang, and Qi Xiong. It has gained popularity in some domains such as image classification, speech recognition, smart city, and healthcare. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. All papers will be peer-reviewed, single-blinded (i.e., please include author names/affiliations/email addresses on your first page). 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. We expect 50-65 people in the workshop. July 21: Clarified that the workshop this year will be held in-person. (Depending on the volume of submissions, we may be able to accommodate only a subset of them.). We expect 60-70 participants. This year the AICS emphasis will be on practical considerations in the real world when deploying AI systems for security with a special focus on convergence of AI and cyber-security in the biomedical field. Attendance is open to all; at least one author of each accepted paper must be virtually present at the workshop. Respect official deadlines - Universit de Montral The goal of this workshop is to offer an opportunity to appreciate the diversity in applications, to draw connections to inform decision optimization across different industries, and to discover new problems that are fundamental to marketplaces of different domains. Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao. Yevgeniy Vorobeychik (Washington University in St. Louis), Bruno Sinopoli (Washington University in St. Louis), Jinghan Yang (Washington University in St. Louis), Bo Li (UIUC), Atul Prakash (University of Michigan), Supplemental Workshop site:https://jinghany.github.io/trase2022/. 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. Xiaojie Guo and Liang Zhao. Pengtao Xie (main contact), Assistant Professor, University of California, San Diego, pengtaoxie2008@gmail.com Engineer Ln, San Diego, CA 92161 (Tel)4123206230, Marinka Zitnik, Assistant Professor, Harvard University, marinka@hms.harvard.edu 10 Shattuck Street, Boston, MA 02115 (Tel)6503086763, Byron Wallace, Assistant Professor, Northeastern University, byron@ccs.neu.edu 177 Huntington Ave, Boston, MA 02115 (Tel)4135120352, Eric P. Xing, Professor, Carnegie Mellon University, epxing@cs.cmu.edu 5000 Forbes Ave, Pittsburgh, PA 15213 (Tel)4122682559, Ramtin Hosseini, PhD Student, University of California, San Diego, rhossein@eng.ucsd.edu (Tel) 3104293825, Ethics and fairness in autonomous systems, Robust robotic design, particularly of autonomous drones and/or vehicles. You may file an application just the same, but Universit de Montral cannot guarantee that it will respond quickly enough for you to be able to complete all the formalities required to study in Quebec. It provides an international forum . In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. The 11th International Conference on Learning Representations (ICLR 2023), accepted. Saliency-Augmented Memory Completion for Continual Learning. . The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners.
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