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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. There is a need for the research community to develop novel solutions for these practical issues. Babies learn their first language through listening, talking, and interacting with adults. Please email to Lingfei Wu: lwu@email.wm.edu for any query. Examples of the datasets which may be considered are the DBTex Radiology Mammogram dataset and the Johns Hopkins COVID-19 case reports. 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. All submissions will be peer-reviewed. We collaborate with Saudi Aramco to use machine learning for simulating oil and water flows, . Washington DC, USA. By clicking Accept All, you consent to the use of ALL the cookies. search, ranking, recommendation, and personalization. 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. 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. ACM RecSys 2022 will be held in Seattle, USA, from September 18 - 23, 2022. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. 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. Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. Virtual . Such systems are better modeled by complex graph structures such as edge and vertex labeled graphs (e.g., knowledge graphs), attributed graphs, multilayer graphs, hypergraphs, temporal/dynamic graphs, etc. 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! 1-39, November 2016. 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. Junxiang Wang, Hongyi Li, Liang Zhao. Knowledge Discovery and Data Mining is an interdisciplinary area focusing upon methodologies and applications for extracting useful knowledge from data [1] . 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. 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. Published March 4, 2023 4:51 a.m. PST. Some will be selected for spotlight talks, and some for the poster session. 2022. It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: KDD 2022. How to do good research, Get it published in SIGKDD and get it cited! We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. ICLR 2022 Meeting Dates The Tenth annual conference is held Mon. Submissions introducing interesting experimental phenomena and open problems of optimal transport and structured data modeling are welcome as well. SIGMOD 2022 adheres to the ACM Policy Against Harassment. This workshop aims to explore and advance the current state of research and practice, including but not limited to the following topics: In addition to the invited talks and the panel discussion on topics related to Document Intelligence, the workshop program will include paper sessions which provides an opportunity to present peer-reviewed work on the topic related to Document Intelligence. "Efficient Global String Kernel with Random Features: Beyond Counting Substructures", 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. arXiv preprint arXiv:2302.02093 (2023). Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. How can we engineer trustable AI software architectures? 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. Submissions will be peer reviewed, single-blinded. Submission URL:https://easychair.org/conferences/?conf=rl4edaaai22. The PAKDD is one of the longest established and leading international conferences in the areas of data mining and knowledge discovery. The following paper categories are welcome: Submission site:https://sites.google.com/view/eaai-ws-2022/call, Silvia Tulli (Dept. Data mining systems and platforms, and their efficiency, scalability, security and privacy. Submission instructions will be available at the workshop web page. It provides an international forum . 3434-3440, Melbourne, Australia, Aug 2017. Aug 14-18. Deep Geometric Neural Networks for Spatial Interpolation. This workshop seeks to explore new ideas on AI safety with particular focus on addressing the following questions: Contributions are sought in (but are not limited to) the following topics: To deliver a truly memorable event, we will follow a highly interactive format that will include invited talks and thematic sessions. Out of these, around 20~30 papers are accepted. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. Hence, this workshop will focus on introducing research progress on applying AI to education and discussing recent advances of handling challenges encountered in AI educational practice. [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. Deep Graph Learning for Circuit Deobfuscation. Innovation, Service, and Rising Star Awards. We allow papers that are concurrently submitted to or currently under review at other conferences or venues. Saliency-regularized Deep Multi-task Learning. 4. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. The submissions must follow the formatting guidelines for AAAI-22. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. Universit de MontralOffice of Admissions and RecruitmentC. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. We have the following keynote speakers confirmed: Andreas Holzinger (Medical Univ. Recently self-supervised approaches for speech/audio processing are also gaining attention. 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. The 48th International Conference on Parallel Processing (ICPP 2019), (acceptance rate: 20%), accepted, Kyoto, Japan. California, United Stes. Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji and Charu Aggarwal. ML-guided rare event modeling and system uncertainty quantification, Development of software, libraries, or benchmark datasets, and. Yuyang Gao, Tanmoy Chowdhury (co-first author), Lingfei Wu, Liang Zhao. The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. "Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework",The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. Xiaojie Guo, Yuanqi Du, Liang Zhao. The cookie is used to store the user consent for the cookies in the category "Analytics". We are soliciting submissions of short papers in PDF format and formatted according to the Standard ACM Conference Proceedings Template. The thematic sessions will be structured into short pitches and a common panel slot to discuss both individual paper contributions and shared topic issues. job seekers, employers, recruiters and job agents. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. IEEE Transactions on Information Forensics and Security (TIFS), (impact factor: 7.178), accepted. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. Liang Zhao, Jiangzhuo Chen, Feng Chen, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. Neil T. Heffernan, Worcester Polytechnic Institute (Worcester, MA, USA), Andrew S. Lan, University of Massachusetts Amherst (Amherst, MA, USA), Anna N. Rafferty, Carleton College (Northfield, MN, USA), Adish Singla, Max Planck Institute for Software Systems (Saarbrucken, Germany). Accepted contributions will be made publicly available as non-archival reports, allowing future submissions to archival conferences or journals. 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. Accepted submissions will be notified latest by August 7th, 2022. The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. Continuous V&V and predictability of AI safety properties, Runtime monitoring and (self-)adaptation of AI safety, Accountability, responsibility and liability of AI-based systems, Avoiding negative side effects in AI-based systems, Role and effectiveness of oversight: corrigibility and interruptibility, Loss of values and the catastrophic forgetting problem, Confidence, self-esteem and the distributional shift problem, Safety of AGI systems and the role of generality, Self-explanation, self-criticism and the transparency problem, Regulating AI-based systems: safety standards and certification, Human-in-the-loop and the scalable oversight problem, Experiences in AI-based safety-critical systems, including industrial processes, health, automotive systems, robotics, critical infrastructures, among others. Computer Communications, (impact factor: 3.34), Elsevier, vo. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. We invite thought-provoking submissions and talks on a range of topics in these fields. 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. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. 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. [paper] 25-50 attendees including invited speakers and accepted papers. 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. ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices. As for the Kraken, they made one trade a month ago to acquire a seventh defenceman, Jaycob Megna and did nothing else (from 'Kraken remain quiet as NHL trade deadline passes,' The Seattle . The consideration and experience of adversarial ML from industry and policy making. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. 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. 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. However, most models and AI systems are built with conservative operating environment assumptions due to regulatory compliance concerns. Papers can be submitted here as an extended abstract (4 pages limit excluding references) or a short paper (6 pages limit excluding references). 10, pp. Web applications along with text processing programs are increasingly being used to harness online data and information to discover meaningful patterns identifying emerging health threats. For research track papers and applied data science track papers. ISBN: 978-981-16-6053-5. However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. Deep learning and statistical methods for data mining. 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/. 25, 2022: We have announced Call for Nominations: , Mar. upon methodologies and applications for extracting useful knowledge from data [1]. Whats more, various AI based models are trained on massive student behavioral and exercise data to have the ability to take note of a students strengths and weaknesses, identifying where they may be struggling. We welcome attendance from individuals who do not have something theyd like to submit but who are interested in RL4ED research. Deep Spatial Domain Generalization. ACM, New York, NY, USA, 10 pages. 29, no. IEEE, 2014. KDD 2022 : Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. Template guidelines are here:https://www.acm.org/publications/proceedings-template. 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. Participants in the hack-a-thon will be asked to either register as a team or be randomly assigned to a team after registration. ASPLOS 2023 will be moving to three submission deadlines. In the coronavirus era, requiring many schools to move to online learning, the ability to give feedback at scale could provide needed support to teachers. This 1-day workshop will include a mixture of invited speakers, panels (including discussion with the audience), and presentations from authors of accepted submissions. The topics for AIBSD 2022 include, but are not limited to: This one-day workshop will include invited talks from keynote speakers, and oral/spotlight presentations of the accepted papers. Conference stats are visualized below for a straightforward comparison. Lyle Unga (University of Pennsylvania, ungar@cis.upenn.edu), Rahul Ladhania* (University of Michigan, ladhania@umich.edu, primary contact), Linnea Gandhi (University of Pennsylvania, lgandhi@wharton.upenn.edu), Michael Sobolev (Cornell Tech, michael.sobolev@cornell.edu), Supplemental workshop site:https://ai4bc.github.io/ai4bc22/, For any questions, please reach out to us at ai4behaviorchange at gmail dot com. Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2021), (acceptance rate: 21.0%), accepted. An Invertible Graph Diffusion Model for Source Localization. The workshop page ishttps://sites.google.com/view/aaaiwfs2022, and it will include the most up-to-date information, including the exact schedule. Naftali Cohen (JP Morgan Chase & New York University), Eren Kurshan (Bank of America & Columbia University), Senthil Kumar (Capital One), Susan Tibbs (Financial Institutions Regulatory Authority, FINRA), Tucker Balch (JP Morgan Chase & Georgia Institute of Technology), and Kevin Compher (Securities Exchange Commission). Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. Some of the key questions to be explored include: The workshop will take place in person and will span over one day. These cookies will be stored in your browser only with your consent. While a variety of research has advanced the fundamentals of document understanding, the majority have focused on documents found on the web which fail to capture the complexity of analysis and types of understanding needed across business documents. 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. 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. 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. We consider submissions that havent been published in any peer-reviewed venue (except those under review). Knowledge Discovery and Data Mining is an interdisciplinary area focusing "The EMBERS architecture for streaming predictive analytics." A challenge is how to integrate people into the learning loop in a way that is transparent, efficient, and beneficial to the human-AI team as a whole, supporting different requirements and users with different levels of expertise. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. Given the ever-increasing role of the World Wide Web as a source of information in many domains including healthcare, accessing, managing, and analyzing its content has brought new opportunities and challenges. There were two workshops on similar topics hosted at ICML 2020 and NeurIPS 2020, and both workshops observed positive feedback and overwhelming participation. Pourya Hoseinip, Liang Zhao, and Amarda Shehu. Topics of interest in the biomedical space include: Topics of general interest to cyber-security include: Submission site:https://easychair.org/conferences/?conf=aics22, Tamara Broderick (MIT CSAIL, tamarab@mit.edu), James Holt (Laboratory for Physical Sciences, USA, holt@lps.umd.edu), Edward Raff (Booz Allen Hamilton, USA, Raff_Edward@bah.com), Ahmad Ridley (National Security Agency), Dennis Ross (MIT Lincoln Laboratory, USA, dennis.ross@ll.mit.edu), Arunesh Sinha (Singapore Management University, Singapore, aruneshs@smu.edu.sg), Diane Staheli (MIT Lincoln Laboratory, USA, diane.staheli@ll.mit.edu), William W. Streilein (MIT Lincoln Laboratory, USA, wws@ll.mit.edu), Milind Tambe (Harvard University, USA, milind_tambe@harvard.edu), Yevgeniy Vorobeychik (Washington University in Saint Louis, USA, eug.vorobey@gmail.com) Allan Wollaber (MIT Lincoln Laboratory, USA, Allan.Wollaber@ll.mit.edu), Supplemental workshop site:http://aics.site/. Proposals of technical talk (up to one-page abstract including short Bio of the main speaker). 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. If these formalities are not completed in time, you will have to file a new application at a later date. We also invite papers that have been published at other venues to spark discussions and foster new collaborations. No supplement is allowed for extended abstracts. https://doi.org/10.1007/s10707-019-00376-9. 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. iDetective: An Intelligent System for Automatic Identification of Key Actors in Online Hack Forums. Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. By registering, you agree to receive emails from UdeM. Application fees are not refundable. 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. This workshop wants to emphasize on the importance of integrative paradigms for solving the new wave of AI applications. Factorized Deep Generative Models for End-to-End Trajectory Generation with Spatiotemporal Validity Constraints. We encourage all the teams who participated in the challenge to join the workshop. Spatial Event Forecasting in Social Media with Geographically Hierarchical Regularization. of London). 1503-1512, Aug 2015. Are you sure you want to create this branch? Submitted papers will be assessed based on their novelty, technical quality, potential impact, and clarity of writing. Nowadays, machine learning solutions are widely deployed. These research trends inform the need to explore the intersection of AI with behavioral science and causal inference, and how they can come together for applications in the social and health sciences. Brave new ideas to learn AI models under bias and scarcity. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. 1059-1072, May 1 2017. At least one author of each accepted submission must register and present the paper at the workshop. : 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. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. information bottleneck principle). [Bests of ICDM]. Submissions may consist of up to 7 pages of technical content plus up to two additional pages solely for references. Yuanqi Du, Xiaojie Guo, Yinkai Wang, Amarda Shehu, Liang Zhao. In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. The academic session will focus on most recent research developments on GNNs in various application domains. We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. We are excited to continue promoting innovation in self-supervision for the speech/audio processing fields and inspiring the fields to contribute to the general machine learning community. Disentangled Spatiotemporal Graph Generative Model. Our intent is to facilitate new AI/ML advances for core engineering design, simulation, and manufacturing. For example, AI tools are built to ease the workload for teachers. The program of the workshop will include invited talks, paper presentations and a panel discussion. Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. 8 pages), short (max. Papers must be in PDF format, in English, and formatted according to the AAAI template. 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. Tips for Doing Good DM Research & Get it Published! Jos Miguel Hernndez-Lobato, University of CambridgeProf. Knowledge Discovery and Data Mining. However, the use of rich data sets also raises significant privacy concerns: They often reveal personal sensitive information that can be exploited, without the knowledge and/or consent of the involved individuals, for various purposes including monitoring, discrimination, and illegal activities. Graph neural networks on node-level, graph-level embedding, Joint learning of graph neural networks and graph structure, Learning representation on heterogeneous networks, knowledge graphs, Deep generative models for graph generation/semantic-preserving transformation, Graph2seq, graph2tree, and graph2graph models, Spatial and temporal graph prediction and generation, Learning and reasoning (machine reasoning, inductive logic programming, theory proving), Natural language processing (information extraction, semantic parsing, text generation), Bioinformatics (drug discovery, protein generation, protein structure prediction), Reinforcement learning (multi-agent learning, compositional imitation learning), Financial security (anti-money laundering), Cybersecurity (authentication graph, Internet of Things, malware propagation), Geographical network modeling and prediction (Transportation and mobility networks, social networks), Computer vision (object relation, graph-based 3D representations like mesh), Lingfei Wu (JD.Com Silicon Valley Research Center),lwu@email.wm.edu, 757-634-5455, https://sites.google.com/a/email.wm.edu/teddy-lfwu/, Jian Pei (Simon Fraser University), jian_pei@sfu.ca, 778-782-6851, https://sites.google.com/view/jpei/jian-peis-homepage, Jiliang Tang (Michigan State University), tangjili@msu.edu, 408-744-2053, https://www.cse.msu.edu/~tangjili/, Yinglong Xia (Facebook AI), yinglongxia@gmail.com, 213-309-9908, https://sites.google.com/site/yinglongxia/, Xiaojie Guo (JD.Com Silicon Valley Research Center), Xguo7@gmu.edu, 571-224-5527, https://sites.google.com/view/xiaojie-guo-personal-site, Sutanay Choudhury (Pacific Northwest National Lab), Stephan Gnnemann (Technical University of Munich), Shen Wang, (University of Illinois at Chicago), Yizhou Sun (University of California, Los Angeles), Lingfei Wu (JD.Com Silicon Valley Research Center), Zhan Zheng (Washington University in St. Louis), Feng Chen (University at Albany State University of New York), Development of corpora and annotation guidelines for multimodal fact checking, Computational models for multimodal fact checking, Development of corpora and annotation guidelines for multimodal hate speech detection and classification, Computational models for multimodal hate speech detection and classification, Analysis of diffusion of Multimodal fake news and hate speech in social networks, Understanding the impact of the hate content on specific groups (like targeted groups), Fake news and hate speech detection in low resourced languages, Vulnerability, sensitivity and attacks against ML, Adversarial ML and adversary-based learning models, Case studies of successful and unsuccessful applications of ML techniques, Correctness of data abstraction, data trust, Choice of ML techniques to meet security and quality, Size of the training data, implied guaranties, Application of classical statistics to ML systems quality, Sensitivity to data distribution diversity and distribution drift, The effect of labeling costs on solution quality (semi-supervised learning), Software engineering aspects of ML systems and quality implications, Testing of the quality of ML systems over time, Quality implication of ML algorithms on large-scale software systems, Explainable/Interpretable Machine Learning, Fairness, Accountability and Transparency, Interactive Teaching Strategies and Explainability, Novel Research Contribution describing original methods and/or results (6 pages plus references), Surveys summarizing and organizing recent research results (up to 8 pages plus references), Demonstrations detailing applications of research findings, and/or debating relevant challenges and issues in the field (4 pages plus references), Constraint satisfaction and programming (CP), (inductive) logic programming (LP and ILP), Learning with Multi-relational graphs (alignment, knowledge graph construction, completion, reasoning with knowledge graphs, etc.

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