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. For further information, please have a look at the call for contributions. Topics include but not limited to: Large-scale and novel targeting technologies, Fraud, fairness, explainability and privacy, Intelligent assistants in job hunting and hiring automation, Large-scale and high performing data infrastructure, data analysis and tooling, Economics and causal inference in online jobs marketplace, Large-scale analytics of user behaviors in online jobs marketplace. 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. in Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), research track, (acceptance rate: 19.4%), Sydney, Australia, pp. Attendance is open to all registered participants. However, ML systems may be non-deterministic; they may re-use high-quality implementations of ML algorithms; and, the semantics of models they produce may be incomprehensible. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. For questions on submission and the workshop, please send email through the following link: Track 1: Tony Qin (Lyft), Rui Song (NC State & Amazon), Hongtu Zhu (UNC), Michael Jordan (Berkeley), Track 2: Liangjie Hong (LinkedIn), Mohammed Korayem (CareerBuilder), Haiyan Luo (Indeed). KDD is the premier Data Science conference. 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. We also welcome submissions that are currently under consideration in such archival venues. 963-971, Apr-May 2015. 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. This AAAI-22 workshop on AI for Decision Optimization (AI4DO) will explore how AI can be used to significantly simplify the creation of efficient production level optimization models, thereby enabling their much wider application and resulting business values.The desired outcome of this workshop is to drive forward research and seed collaborations in this area by bringing together machine learning and decision-making from the lens of both dynamic and static optimization models. 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. 2022. Integration of AI-based approaches with engineering prototyping and manufacturing. The main goal of the dialog system technology challenge (DSTC) workshop is to share the result of five main tracks of the tenth dialog system technology challenge (DSTC10). Recently self-supervised approaches for speech/audio processing are also gaining attention. iDetective: An Intelligent System for Automatic Identification of Key Actors in Online Hack Forums. Counter-intuitive behaviors of ML models will largely affect the public trust on AI techniques, while a revolution of machine learning/deep learning methods may be an urgent need. The submission website ishttps://cmt3.research.microsoft.com/OTSDM2022. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. This policy also applies to papers that overlap substantially in technical content with papers previously published, accepted, or under review. Xiaosheng Li, Jessica Lin, Liang Zhao. Online marketplaces exist in a diverse set of domains and industries, for example, rideshare (Lyft, DiDi, Uber), house rental (Airbnb), real estate (Beke), online retail (Amazon, Ebay), job search (LinkedIn, Indeed.com, CareerBuilder), and food ordering and delivery (Doordash, Meituan). 4. Knowledge Discovery and Data Mining is an interdisciplinary area focusing 2022. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. If the admission deadline for international applicants is past, we suggest that you choose another session to begin your studies. Instead of grading each piece of work individually, which can take up a bulk of extra time, intelligent scoring tools allow teachers the ability to have their students work automatically graded. ETA (expected time-of-arrival) prediction. I recommend highly motivated students to reach out to me way earlier than the admission deadline, and figure out a research project project with me, with the goal of a publication. Topics of interest include but are not limited to: (1) Survey papers summarizing recent advances in RL with applicability to ED; (2) Developing toolkits and datasets for applying RL methods to ED; (3) Using RL for online evaluation and A/B testing of different intervention strategies in ED; (4) Novel applications of RL for ED problem settings; (5) Using pedagogical theories to narrow the policy space of RL methods; (6) Using RL methodology as a computational model of students in open-ended domains; (7) Developing novel offline RL methods that can efficiently leverage historical student data; (8) Combining statistical power of RL with symbolic reasoning to ensure the robustness for ED. "Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data" The 26th ACM International Conference on Information and Knowledge Management (CIKM 2017) , (acceptance rate: 21%), pp. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. Molecules, (impact factor: 4.411), accepted. To adapt SSL frameworks to build effective human-centric deep learning solutions for human-centric data, a number of key challenges and opportunities need to be explored. Knowledge Discovery and Data Mining. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. 29, no. We allow both short (2-4 pages) and long papers (6-8 pages) papers. 2022. 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 Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. The workshop attracted about 100 attendees. SDU is expected to host 50-60 attendees. Deep Graph Translation. Information theoretic quantities (entropy, mutual information, divergence) estimation, Information theoretic methods for out-of-domain generalization and relevant problems (such as robust transfer learning and lifelong learning), Information theoretic methods for learning from limited labelled data, such as few-shot learning, zero-shot learning, self-supervised learning, and unsupervised learning, Information theoretic methods for the robustness of DNNs in AI systems, The explanation of deep learning models (in AI systems) with information-theoretic methods, Information theoretic methods in different AI applications (e.g., NLP, healthcare, robotics, finance). The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. Manuscripts must be submitted as PDF files viaEasyChair online submission system. Theoretical or empirical studies focusing on understanding why self-supervision methods work for speech and audio. A new and comprehensive view of AI Safety must cover a wide range of AI paradigms, including systems that are application-specific as well as those that are more general, considering potentially unanticipated risks. All papers must be submitted in PDF format using the AAAI-22 author kit. December 2020, July 21: Clarified that the workshop this year will be held, June 20: Paper notification is now extended to, Paper reviews are underway! Authors are strongly encouraged to make data and code publicly available whenever possible. Attendance is open to all registered participants. Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, Girish Chowdhary (University of Illinois, Urbana Champaign), Baskar Ganapathysubramanian (Iowa State University; contact: baskarg@iastate.edu), George Kantor (Carnegie Mellon University), Soumyashree Kar (Iowa State University), Koushik Nagasubramanian (Iowa State University), Soumik Sarkar (Iowa State University), Katia Sycara (Carnegie Mellon University), Sierra Young (North Carolina State University), Alina Zare (University of Florida, Gainesville), Supplemental workshop site:https://aiafs-aaai2022.github.io/. ), 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). Disentangled Spatiotemporal Graph Generative Model. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. LOG 2022 LOG '22 . 2, no. VDS will bring together domain scientists and methods researchers (including data mining, visualization, usability and HCI, data management, statistics, machine learning, and software engineering) to discuss common interests, talk about practical issues, and identify open research problems in visualization in data science. Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting. We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. For research track papers and applied data science track papers. Rather than studying robustness with respect to particular ML algorithms, our approach will be to explore robustness assurance at the system architecture level, during both development and deployment, and within the human-machine teaming context. Question answering on business documents. The goal of this workshop is to bring together the optimal transport, artificial intelligence, and structured data modeling, gathering insights from each of these fields to facilitate collaboration and interactions. "EMBERS at 4 years:Experiences operating an Open Source Indicators Forecasting System." By registering, you agree to receive emails from UdeM. Algorithms and theories for explainable and interpretable AI models. 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 IEEE International Conference on Data Mining (ICDM 2018), regular paper (acceptance rate: 8.9%), Singapore, Dec 2018, accepted. Xiaojie Guo, Yuanqi Du, Liang Zhao. "Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System." It provides an international forum . This is a one-day workshop, planned with a 10-minute opening, 6 invited keynotes, ~6 contributed talks, 2 poster sessions, and 2 panel discussions. Kyoto . CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. Knowledge and Information Systems (KAIS), (impact factor: 2.936), accepted. The first AAAI Workshop on AI for Design and Manufacturing, ADAM, aims to bring together researchers from core AI/ML, design, manufacturing, scientific computing, and geometric modeling. Deep Generative Model for Periodic Graphs. Extended abstract up to 2 pages are also welcome. arXiv preprint arXiv:2002.11867 (2021), Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International NOTE: May 19: Notification. Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. But opting out of some of these cookies may affect your browsing experience. arXiv preprint arXiv:2212.03954 (2022). This date takes priority over those shown below and could be extended for some programs. information bottleneck principle). The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. Paper Final Version Due: Monday August 1, 2022. The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2021), (acceptance rate: 23.6%), accepted. 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 . Yuyang Gao, Giorgio Ascoli, Liang Zhao. 9, no. ADMM for Efficient Deep Learning with Global Convergence. Robust Regression via Online Feature Selection under Adversarial Data Corruption. Information-theoretic approaches provide a novel set of tools that can expand the scope of classical approaches to causal inference and discovery problems in a variety of applications. Position papers are welcome. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu. Conference stats are visualized below for a straightforward comparison. International Journal of Digital Earth, (impact factor: 3.097), 25 Aug 2020, https://doi.org/10.1080/17538947.2020.1809723. These complex demands have brought profound implications and an explosion of interest for research into the topic of this workshop, namely building practical AI with efficient and robust deep learning models. A striking feature of much of this recent work is the application of new theoretical and computational techniques for comparing probability distributions defined on spaces with complex structures, such as graphs, Riemannian manifolds and more general metric spaces. Each accepted paper presentation will be allocated between 15 and 20 minutes. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. algorithms applied to the above topics: deep learning, reinforcement learning, multi-armed bandits, causal inference, mathematical programming, and stochastic optimization. for causal estimation in behavioral science. Martin Michalowski, PhD, FAMIA (Co-chair), University of Minnesota; Arash Shaban-Nejad, PhD, MPH (Co-chair), The University of Tennessee Health Science Center Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics; Simone Bianco, PhD (Co-chair), IBM Almaden Research Center; Szymon Wilk, PhD, Poznan University of Technology; David L. Buckeridge, MD, PhD, McGill University; John S. Brownstein, PhD, Boston Childrens Hospital, Workshop URL:http://w3phiai2022.w3phi.com/. At least one author of each accepted submission must be present at the workshop. 1, Sec. 1503-1512, Aug 2015. Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2021), (acceptance rate: 21.0%), accepted. Besides academia, many companies and institutions are researching on topics specific to their particular domains. Liang Gou, Bosch Research (IEEE VIS liaison), Claudia Plant, University of Vienna (KDD liaison), Alvitta Ottley, Washington University, St. Louis, Junming Shao, University of Electronic Science and Technology of China, Visualization in Data Science (VDS at ACM KDD and IEEE VIS), Visualization in Data Science (VDS at ACM KDD and IEEE VIS). Thirty-First AAAI Conference on Artificial Intelligence, pp. Multilingual document understanding methods and frameworks. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . Important Dates. Liang Zhao, Feng Chen, and Yanfang Ye. 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. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. The cookie is used to store the user consent for the cookies in the category "Analytics". 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. Oct 14, 2021: Abstract Deadline. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. Submissions that are already accepted or under review for another conference or already accepted for a journal are not accepted. How can we make AI-based systems more ethically aligned? 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." Reasons include: (1) a lack of certification of AI for security, (2) a lack of formal study of the implications of practical constraints (e.g., power, memory, storage) for AI systems in the cyber domain, (3) known vulnerabilities such as evasion, poisoning attacks, (4) lack of meaningful explanations for security analysts, and (5) lack of analyst trust in AI solutions. Participants are welcomed to submit their system reports to be presented in the workshop. Guangji Bai, Chen Ling, Liang Zhao. Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu. 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. Fang Jin, Wei Wang, Liang Zhao, Edward Dougherty, Yang Cao, Chang-Tien Lu, and Naren Ramakrishnan. However, you may visit "Cookie Settings" to provide a controlled consent. 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 . In addition, broad deployment of ML software in networked systems inevitably exposes ML software to attacks. All the workshop chairs, most of the Committees, and the authors of the accepted papers will attend the workshop also. job seekers, employers, recruiters and job agents. Novel mechanisms for eliciting and consuming user feedback, recommender, structured and generative models, concept acquisition, data processing, optimization; HCI and visualization challenges; Analysis of human factors/cognition and user modelling; Design, testing and assessment of IML systems; Studies on risks of interaction mechanisms, e.g., information leakage and bias; Business use cases and applications. Even in cases where one is able to collect data, there are inherently many kinds of biases in this process, leading to biased models. 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. IEEE Computer (impact factor: 3.564), vo. Gabriel Pedroza (CEA LIST), Jos Hernndez-Orallo (Universitat Politcnica de Valncia, Spain), Xin Cynthia Chen (University of Hong Kong, China), Xiaowei Huang (University of Liverpool, UK), Huascar Espinoza (KDT JU, Belgium), Mauricio Castillo-Effen (Lockheed Martin, USA), Sen higeartaigh (University of Cambridge, UK), Richard Mallah (Future of Life Institute, USA), John McDermid (University of York, UK), Supplemental workshop site:http://safeaiw.org/. Deep Graph Learning for Circuit Deobfuscation. The study of complex graphs is a highly interdisciplinary field that aims to study complex systems by using mathematical models, physical laws, inference and learning algorithms, etc. In recent years, machine learning techniques (e.g. Papers will be submitted to OpenReview system: Waiting for approval,https://openreview.net/forum?id=6uMNTvU-akO, Workshop Chair:Parisa Kordjamshidi, +1-2174187004, kordjams@msu.edu, Organizing Committee:Parisa Kordjamshidi (Michigan State University, kordjams@msu.edu), Behrouz Babaki (Mila/HEC Montreal, behrouz.babaki@mila.quebec), Sebastijan Dumani (KU Leuven, sebastijan.dumancic@cs.kuleuven.be), Alex Ratner (University of Washington, ajratner@cs.washington.edu), Hossein Rajaby Faghihi (Michigan State University, rajabyfa@msu.edu), Hamid Karimian (Michigan State University, karimian@msu.edu), Organizing Committee:Dan Roth (University of Pennsylvania, danroth@seas.upenn.edu) and Guy Van Den Broeck (University of California Los Angeles, guyvdb@cs.ucla.edu), Supplemental workshop site:https://clear-workshop.github.io. 8 pages), short (max. 2020. Note: The workshop is a collaboration between NASSMA organisation, Deepmind and UM6P. Panel discussion: Interactive Q&A session with a panel of leading researchers. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. Call for Participation The 3rd KDD Workshop on Data-driven Humanitarian Mapping and Policymaking solicits research papers, case studies, vision papers, software demos, and extended abstracts. Xiaojie Guo, Yuanqi Du, Liang Zhao. Federated learning (FL) is one promising machine learning approach that trains a collective machine learning model using sharing data owned by various parties. Big data Journal (impact factor: 1.489), vo. Information extraction and information retrieval for scientific documents; Question answering and question generation for scholarly documents; Word sense disambiguation, acronym identification and expansion, and definition extraction; Document summarization, text mining, document topic classification, and machine reading comprehension for scientific documents; Graph analysis applications including knowledge graph construction and representation, graph reasoning and query knowledge graphs; Biomedical image processing, scientific image plagiarism detection, and data visualization; Code/Pseudo-code generation from text and im-age/diagram captioning, New language understanding resources such as new syn-tactic/semantic parsers, language models or techniques to encode scholarly text; Survey or analysis papers on scientific document under-standing and new tasks and challenges related to each scientific domain; Factuality, data verification, and anti-science detection. Fine tuning a neural network is very time consuming and far from optimal. We invite submission of papers describing innovative research on all aspects of knowledge discovery and data science, ranging from theoretical foundations to novel models and algorithms for data science problems in science, business, medicine, and engineering. The objective of this workshop is to discuss the winning submissions of the Submissions to the Amazon KDD Cup 2022 issingle-blind (author names and affiliations should be listed). Automatic fact/claim verification has recently become a topic of interest among diverse research communities. This cookie is set by GDPR Cookie Consent plugin. Association for the Advancement of Artificial Intelligence, The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada. An Invertible Graph Diffusion Model for Source Localization. This cookie is set by GDPR Cookie Consent plugin. Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. ", ACM Transactions on Spatial Algorithms and Systems (TSAS), (Acceptance Rate: 11%), Volume 2 Issue 4, Acticle No. URL: https://sites.google.com/view/kdd22onlinemarketplaces Call For Papers (Submission deadline: June3, 2022) Participants in the hack-a-thon will be asked to either register as a team or be randomly assigned to a team after registration. Welcome to the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2022), which will be held in Chengdu, China on May 16-19, 2022. Dataset(s) will be provided to hack-a-thon participants. The review process is double-blind, and we follow the Conflict of Interest Policy for ACM Publications. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. Submission URL:https://easychair.org/my/conference?conf=vtuaaai2022. [Best Poster Runner-Up Award]. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. However, research in the AI field also shows that their performance in the wild is far from practical due to the lack of model efficiency and robustness towards open-world data and scenarios. 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. Exploring the limits of self-supervised learning approaches for speech and audio processing, for example, adverse environment conditions, multiple languages, or generalization across downstream tasks. We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. Submissions of technical papers can be up to 7 pages excluding references and appendices. Submissions are due by 12 November 2021. Rabat, Morocco . 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/. The workshop welcomes the submission of work on, but not limited to, the following research directions. 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/. 1-11, Feb 2016. DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. Workshops are one day unless otherwise noted in the individual descriptions. and deep learning techniques (e.g. By entering your email, you consent to receive communications from UdeM. Submissions of technical papers can be up to 7 pages excluding references and appendices. 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. KDD 2022 -ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). Dynamic Tracking and Relative Ranking of Airport Threats from News and Social Media. Registration in each workshop is required by all active participants, and is also open to all interested individuals. https://doi.org/10.1007/s10707-019-00376-9. Yuanqi du, George Mason University, USA; Jian Pei, Simon Fraser University, Canada; Charu Aggarwal, IBM Research AI, USA; Philip S. Yu, University of Illinois at Chicago, USA; Xuemin Lin, University of New South Wales, Australia; Jiebo Luo, University of Rochester, USA; Lingfei Wu, JD.Com Silicon Valley Research Center, USA; Yinglong Xia, Facebook AI, USA; Jiliang Tang, Michigan State University, USA; Peng Cui, Tsinghua University, China; William L. Hamilton, McGill University, Canada; Thomas Kipf, University of Amsterdam, Netherlands, Workshop URL:https://deep-learning-graphs.bitbucket.io/dlg-aaai22/.
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