kdd 2022 deadline

Well also host a competition on adversarial ML along with this workshop. Table identification and extraction from business documents. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. Liang Zhao, Junxiang Wang, and Xiaojie Guo. How can we develop solid technical visions and new paradigms about AI Safety? Submissions can be original research contributions, or abstracts of papers previously submitted to top-tier venues, but not currently under review in other venues and not yet published. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 20%=174/870), short paper, to appear, 2022. Federated learning (FL) is one promising machine learning approach that trains a collective machine learning model using sharing data owned by various parties. Integration of neuro and symbolic approaches. VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. As far as we know, we are the first workshop to focus on practical deep learning in the wild for AI, which is of great significance. How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: KDD 2023 August 06-10, 2023. All papers will be peer reviewed, single-blinded. Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting.Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), (acceptance rate: 16.2%), Hawaii, USA, Feb 2019, accepted. 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. 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. Winter. 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/. : 1, Sec. 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. Ranking, acceptance rate, deadline, and publication tips. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. We aim to bring together researchers in AI, healthcare, medicine, NLP, social science, etc. These cookies will be stored in your browser only with your consent. 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. Representation Learning on Spatial Networks. There will be live Q&A sessions at the end of each talk and oral presentation. It is anticipated that this will be an in-person workshop, subject to changing travel restrictions and health measures. A primary reason for this is the inherent long-tailed nature of our world, and the need for algorithms to be trained with large amounts of data that includes as many rare events as possible. What AI safety considerations and experiences are relevant from industry? Detailed information could be found on the website of the workshop. "How events unfold: spatiotemporal mining in social media." This workshop aims to discuss important topics about adversarial ML to deepen our understanding of ML models in adversarial environments and build reliable ML systems in the real world. In spite of substantial research focusing on discovery from news, web, and social media data, its applications to datasets in professional settings such as financial filings and government reports, still present huge challenges. Submit to:https://cmt3.research.microsoft.com/AIBSD2022, Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories, kp388@cornell.edu), Ziyan Wu (UII America, Inc., wuzy.buaa@gmail.com), Supplemental workshop site:https://aibsdworkshop.github.io/2022/index.html. Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, and Chang-Tien Lu. It is expected that one of the authors of accepted contributions will register and attend the workshop to present the work in video in-person in the workshops Paper Sessions. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. How can we engineer trustable AI software architectures? [code] Encore track papers that have been recently published, or accepted for publication in a conference or journal. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. Online Flu Epidemiological Deep Modeling on Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. Manuscripts must be submitted as PDF files viaEasyChair online submission system. 7, no. GNES: Learning to Explain Graph Neural Networks. 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 ). The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. The Conference. Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with human agents. Papers will be peer-reviewed and selected for spotlight and/or poster presentation. Novel AI-enabled generative models for system design and manufacturing. The workshop welcomes the submission of work on, but not limited to, the following research directions. and deep learning techniques (e.g. Interpretable Molecular Graph Generation via Monotonic Constraints. This proposed workshop will build upon successes and learnings from last years successful AI for Behavior Change workshop, and will focus on on advances in AI and ML that aim to (1) design and target optimal interventions; (2) explore bias and equity in the context of decision-making and (3) exploit datasets in domains spanning mobile health, social media use, electronic health records, college attendance records, fitness apps, etc. Integration of probabilistic inference in training deep models. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. Atlanta, Georgia, USA . Conference stats are visualized below for a straightforward comparison. The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2022 (ACM SIGSPATIAL 2022), poster track, to appear, 2022. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. To facilitate KDD related research, we create this repository with: *ICDM has two tracks (regular paper track and short paper track), but the exact statistic is not released, e.g., the split between these two tracks. Meta-learning models from various existing task-specific AI models. The 19th International Conference on Data Mining (ICDM 2019), long paper, (acceptance rate: 9.08%), Beijing, China. 2020. SDU will be a one-day workshop. Positive applications of adversarial ML, i.e., adversarial for good. The industry session will emphasize practical industrial product developments using GNNs. Integrated syntax and semantic approaches for document understanding. Attendance is open to all prior registration to the workshop/conference. KDD 2022. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan. Why did so many AI/ML models fail during the pandemic? We invite thought-provoking submissions and talks on a range of topics in these fields. 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. The growing popularity of NAS methods demonstrates the communitys hunger for better ways of choosing or evolving network architectures that are well-matched to the problem at hand. Interesting challenges in this domain include the drastic increase of work from home or remote work, the imbalance between the demand and supply of the job market, the popularity of independent workers, the capability of helping job seekers on their whole job seeking journey and career development, the different objectives and behaviors of all major stakeholders in the ecosystem, e.g. Ferdinando Fioretto (Syracuse University), Emma Frejinger (Universit de Montral), Elias B. Khalil (University of Toronto), Pashootan Vaezipoor (University of Toronto). IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. Welcome to DLG-KDD'22! - Bitbucket search, ranking, recommendation, and personalization. Junxiang Wang, Junji Jiang, Liang Zhao. 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). Accepted submissions will have the option of being posted online on the workshop website. 625-634, New Orleans, US, Dec 2017. Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. [Best Paper Candidate]. Continuous refinement of AI models using active/online learning. Prediction-time Efficient Classification Using Feature Computational Dependencies. Online . Disease Contact Network. [Best Poster Runner-Up Award]. anomaly detection, and ensemble learning. We received 38 paper submissions and accepted 23 of them. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. 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. It is difficult to expose false claims before they create a lot of damage. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. We will also have a video component for remote participation. Please refer and submit through theLearning Network Architecture During Trainingworkshop website, which has more detailed information. ASPLOS 2023 will be moving to three submission deadlines. Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao. The workshop will focus on the application of AI to problems in cyber-security. "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. The program consists of poster sessions for accepted papers, and invited and spotlight talks. Attendance is open to all registered participants. In the financial services industry particularly, a large amount of financial analysts work requires knowledge discovery and extraction from different data sources, such as SEC filings and industry reports, etc., before they can conduct any analysis. We will receive the paper on the CMT system. Adversarial attacking deep learning systems, Robust architectures against adversarial attacks, Hardware implementation and on-device deployment, Benchmark for evaluating model robustness, New methodologies and architectures for efficient and robust deep learning, December 3, 2021 Acceptance Notification, Applications of privacy-preserving AI systems, Differential privacy: theory and applications, Distributed privacy-preserving algorithms, Privacy preserving optimization and machine learning, Privacy preserving test cases and benchmarks. Submitted papers will be assessed based on their novelty, technical quality, potential impact, and clarity of writing. Expected attendance is 40-50 people. Deep Learning models are at the core of research in Artificial Intelligence research today. Journal of Biomedical Semantics, (impact factor: 1.845), 2018, accepted. Submissions that are already accepted or under review for another conference or already accepted for a journal are not accepted. Geographical Mapping and Visual Analytics for Health Data, Biomedical Ontologies, Terminologies, and Standards, Bayesian Networks and Reasoning under Uncertainty, Temporal and Spatial Representation and Reasoning, Crowdsourcing and Collective Intelligence, Risk Assessment, Trust, Ethics, Privacy, and Security, Computational Behavioral/Cognitive Modeling, Health Intervention Design, Modeling and Evaluation, Applications in Epidemiology and Surveillance (e.g., Bioterrorism, Participatory Surveillance, Syndromic Surveillance, Population Screening), Hybrid methods, combining data driven and predictive forward models, biomedical signal analysis/modeling (EEG, ECG, PPG, EMG, fMRI, IMU, medical/clinical data, etc. We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. in Proceedings of the SIAM International Conference on Data Mining (SDM 2015), (acceptance rate: 22%), Vancouver, BC, pp. There will be about 60~85 people to participate, including the program committee, invited speakers, panelists, authors of accepted papers, winners of the competition and other interested people. Deep Generation of Heterogeneous Networks. AI is one of these transformative technologies that is now achieving great successes in various real-world applications and making our life more convenient and safer. Information extraction from text and semi-structured documents. It does not store any personal data. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. 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. Integration of Deep learning and Constraint programming. Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Submission Site: See the webpagehttps://sites.google.com/view/gclr2022/submissions; for detailed instructions and submission link. 10, pp. Note: The workshop is a collaboration between NASSMA organisation, Deepmind and UM6P. Invited speakers, committee members, authors of the research paper, and the participants of the shared task are invited to attend. The research contributions may discuss technical challenges of reading and interpreting business documents and present research results. We consider submissions that havent been published in any peer-reviewed venue (except those under review). Microsoft Research CMT: https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/ or https://aka.ms/di-2022, Workshop registration will be processed with the main KDD 2022 conference: https://kdd.org/kdd2022/, Standard ACM Conference Proceedings Template, Conflict of Interest Policy for ACM Publications, https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/, Second Document Intelligence Workshop @ KDD 2021, First Document Intelligence Workshop @ NeurIPS 2019, Hamid Motahari, Nigel Duffy, Paul Bennett, and Tania Bedrax-Weiss. 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. Some good examples include recommender systems, clustering, graph mining, Accelerated Gradient-free Neural Network Training by Multi-convex Alternating Optimization. Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang. [materials]. We plan to invite 2-4 keynote speakers from prestigious universities and leading industrial companies. IEEE Transactions on Knowledge and Data Engineerings (TKDE), (impact factor: 6.977), accepted. Award for Artificial Intelligence for the Benefit of Humanity, Patrick Henry Winston Outstanding Educator Award, A Report to ARPA on Twenty-First Century Intelligent Systems, The Role of Intelligent Systems in the National Information Infrastructure, Code of Conduct for Conferences and Events, Request to Reproduce Copyrighted Materials, AAAI Conference on Artificial Intelligence, W1: Adversarial Machine Learning and Beyond, W2: AI for Agriculture and Food Systems (AIAFS), W6: AI in Financial Services: Adaptiveness, Resilience & Governance, W7: AI to Accelerate Science and Engineering (AI2ASE), W8: AI-Based Design and Manufacturing (ADAM) (Half-Day), W9: Artificial Intelligence for Cyber Security (AICS)(2-Day), W10: Artificial Intelligence for Education (AI4EDU), W11: Artificial Intelligence Safety (SafeAI 2022)(1.5-Day), W12: Artificial Intelligence with Biased or Scarce Data, W13: Combining Learning and Reasoning: Programming Languages, Formalisms, and Representations (CLeaR), W14: Deep Learning on Graphs: Methods and Applications (DLG-AAAI22), W15: DE-FACTIFY :Multi-Modal Fake News and Hate-Speech Detection, W16: Dialog System Technology Challenge (DSTC10), W17: Engineering Dependable and Secure Machine Learning Systems (EDSMLS 2022) (Half-Day), W18: Explainable Agency in Artificial Intelligence, W19: Graphs and More Complex Structures for Learning and Reasoning (GCLR), W21: Human-Centric Self-Supervised Learning (HC-SSL), W22: Information-Theoretic Methods for Causal Inference and Discovery (ITCI22), W23: Information Theory for Deep Learning (IT4DL), W25: Knowledge Discovery from Unstructured Data in Financial Services (Half-Day), W26: Learning Network Architecture during Training, W27: Machine Learning for Operations Research (ML4OR) (Half-Day), W28: Optimal Transport and Structured Data Modeling (OTSDM), W29: Practical Deep Learning in the Wild (PracticalDL2022), W30: Privacy-Preserving Artificial Intelligence, W31: Reinforcement Learning for Education: Opportunities and Challenges, W32: Reinforcement Learning in Games (RLG), W33: Robust Artificial Intelligence System Assurance (RAISA) (Half-Day), W34: Scientific Document Understanding (SDU) (Half-Day), W35: Self-Supervised Learning for Audio and Speech Processing, W36: Trustable, Verifiable and Auditable Federated Learning, W38: Trustworthy Autonomous Systems Engineering (TRASE-22), W39: Video Transcript Understanding (Half-Day), https://openreview.net/group?id=AAAI.org/2022/Workshop/AdvML, https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, https://easychair.org/conferences/?conf=aaai-2022-workshop, https://rail.fzu.edu.cn/info/1014/1064.htm, https://aaai.org/Conferences/AAAI-22/aaai22call/, https://sites.google.com/view/aaaiwfs2022, https://www.aaai.org/Publications/Templates/AuthorKit22.zip, https://openreview.net/group?id=AAAI.org/2022/Workshop/ADAM, https://easychair.org/conferences/?conf=aics22, https://cmt3.research.microsoft.com/AIBSD2022, https://aibsdworkshop.github.io/2022/index.html, https://openreview.net/forum?id=6uMNTvU-akO, https://easychair.org/conferences/?conf=dlg22, https://deep-learning-graphs.bitbucket.io/dlg-aaai22/, https://cmt3.research.microsoft.com/DSTC102022, https://dstc10.dstc.community/calls_1/call-for-workshop-papers, https://easychair.org/my/conference?conf=edsmls2022, https://sites.google.com/view/edsmls-2022/home, https://sites.google.com/view/eaai-ws-2022/call, https://sites.google.com/view/eaai-ws-2022/topic, https://sites.google.com/view/gclr2022/submissions, https://cmt3.research.microsoft.com/AAAI2022HCSSL/Submission/Index, https://cmt3.research.microsoft.com/ITCI2022, https://easychair.org/conferences/?conf=it4dl, https://easychair.org/conferences/?conf=imlaaai22, https://sites.google.com/view/aaai22-imlw, https://easychair.org/conferences/?conf=kdf22, Learning Network Architecture During Training, https://cmt3.research.microsoft.com/OTSDM2022, https://cmt3.research.microsoft.com/PracticalDL2022, https://cmt3.research.microsoft.com/PPAI2022, https://easychair.org/conferences/?conf=rl4edaaai22, https://sites.google.com/view/raisa-2022/, https://sites.google.com/view/sdu-aaai22/home, https://cmt3.research.microsoft.com/SAS2022, https://easychair.org/conferences/?conf=fl-aaai-22, http://federated-learning.org/fl-aaai-2022/, https://cmt3.research.microsoft.com/TAIH2022, https://easychair.org/conferences/?conf=trase2022, https://easychair.org/my/conference?conf=vtuaaai2022, Symposium on Educational Advances in Artificial Intelligence (EAAI-22), Conference on Innovative Applications of Artificial Intelligence (IAAI-22).

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