Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao. Ranking, acceptance rate, deadline, and publication tips. Deep Geometric Neural Networks for Spatial Interpolation. Paper Submission Deadline: 23:59 on Thursday. 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. The main interest of the proposed workshop is to look at a new perspective of system engineering where multiple disciplines such as AI and safety engineering are viewed as a larger whole, while considering ethical and legal issues, in order to build trustable intelligent autonomy. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. "Knowledge-enhanced Neural Machine Reasoning: A Review." Oilers Outperform Division Rivals at 2023 Trade Deadline Data-driven Humanitarian Mapping and Policymaking Research Multi-objective Deep Data Generation with Correlated Property Control. Research efforts and datasets on text fact verification could be found, but there is not much attention towards multi-modal or cross-modal fact-verification. Thirty-First AAAI Conference on Artificial Intelligence, pp. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Attendance is open to all; at least one author of each accepted paper must be virtually present at the workshop. New theory and fundamentals of AI-aided design and manufacturing. Submission link:https://easychair.org/cfp/raisa-2022, William Streilein, MIT Lincoln Laboratory, 244 Wood St., Lexington, MA, 02420, (781) 981-7200, wws@ll.mit.edu, Olivia Brown (MIT Lincoln Laboratory, Olivia.Brown@ll.mit.edu), Rajmonda Caceres (MIT Lincoln Laboratory, Rajmonda.Caceres@ll.mit.edu), Tina Eliassi-Rad (Northeastern University, teliassirad@northeastern.edu), David Martinez (MIT Lincoln Laboratory, dmartinez@ll.mit.edu), Sanjeev Mohindra (MIT Lincoln Laboratory, smohindra@ll.mit.edu), Elham Tabassi (National Institute of Standards and Technology, elham.tabassi@nist.gov), Workshop URL:https://sites.google.com/view/raisa-2022/. Saliency-Augmented Memory Completion for Continual Learning. Handwritten recognition in business documents. Our preliminary plan for the schedule is as following , DEFACTIFY@AAAI-22 Program [tentative]9:00AM-9:15AMInaugurationA brief summary of the shared tasks number of participants, best results, Session 1 multimodal fact checkingWorkshop papers 9:30AM 10:30AM, 11:00AM 12:00pmInvited talk 1 Prof. Rada Mihalcea, University of Michigan, Session 2 Best 4/5 papers from FACTIFY & MEMOTION shared taskWorkshop papers 1:00PM 2:00PM, 2:00PM 3:30PMInvited talk 2 Prof. LOUIS-PHILIPPE MORENCY, CMU, Session 2 multimodal hate speechWorkshop papers 4:00PM 5:00PM. Liang Zhao, Junxiang Wang, and Xiaojie Guo. 689-698, Barcelona, Spain, Dec 2016. With this in mind, we welcome relevant contributions on the following (and related) topic areas: The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. 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. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. Submission site:https://cmt3.research.microsoft.com/ITCI2022, Murat Kocaoglu, Chair (Purdue University, mkocaoglu@purdue.edu), Negar Kiyavash (EPFL, negar.kiyavash@epfl.ch), Todd Coleman (UCSD, tpcoleman@ucsd.edu), Supplemental workshop site:https://sites.google.com/view/itci22. [paper] KDD 2022 -ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. The extraction, representation, and sharing of health data, patient preference elicitation, personalization of generic therapy plans, adaptation to care environments and available health expertise, and making medical information accessible to patients are some of the relevant problems in need of AI-based solutions. 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. AAAI is pleased to present the AAAI-22 Workshop Program. 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/. ), 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). robust and interpretable natural language processing for healthcare. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. Kaiqun Fu, Taoran Ji, Liang Zhao, and Chang-Tien Lu. KDD: Knowledge Discovery and Data Mining 2024 2023 2022 - WikiCFP The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2022 (ACM SIGSPATIAL 2022), poster track, to appear, 2022. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . ACM, 2014. IEEE Computer (impact factor: 3.564), vo. This cookie is set by GDPR Cookie Consent plugin. Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. It has gained popularity in some domains such as image classification, speech recognition, smart city, and healthcare. It does not store any personal data. 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. Using a social media account will simply make the application process easier: none of your activities on this site will be posted to your profile. 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. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. 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. 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 . Long talks (50 mins):Gabriel Peyr, (Mathematics, CNRS Senior Researcher);Yusu Wang, (Mathematics, Professor in CSE, UCSD);Caroline Uhler, (Statistics and CS, Associate Professor in EECS and IDSS, MIT); Short talks (25mins):Titouan Vayer, (Mathematics, Postdoctoral Researcher at ENS Lyon);Tam Le, (Computer Science, Research Scientist at RIKEN);Dixin Luo, (Computer Science, Assistant Professor in CS, Beijing Institute of Technology). Some will be selected for spotlight talks, and some for the poster session. ITCI22 will be a one-day workshop. California, United Stes. Call for Papers Document Intelligence Workshop @ KDD 2022 Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. 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. The desired LENGTH of the workshop: Full-day (~8 hours). Our topics of interest span over prediction, planning, and decision problems for online marketplaces, including but not limited to. This manual extraction process is usually inefficient, error-prone, and inconsistent. 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. Big data Journal (impact factor: 1.489), vo. 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. Scientific documents such as research papers, patents, books, or technical reports are one of the most valuable resources of human knowledge. Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Jiabin Wang, and Qi Xiong. 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). The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Datasets and Benchmarks Track, accepted. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. At the same time, multimodal hate-speech detection is an important problem but has not received much attention. 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 review process is double-blind, and we follow the Conflict of Interest Policy for ACM Publications. 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. RAISAs systems-level perspective will be emphasized via three main thrusts: AI threat modeling, AI system robustness, explainable AI, system lifecycle attacks, system verification and validation, robustness benchmarks and standards, robustness to black-box and white-box adversarial attacks, defenses against training, operational and inversion attacks, AI system confidentiality, integrity, and availability, AI system fairness and bias. While classical security vulnerabilities are relevant, ML techniques have additional weaknesses, some already known (e.g., sensitivity to training data manipulation), and some yet to be discovered. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. 3434-3440, Melbourne, Australia, Aug 2017. Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang. Adverse event detection by integrating Twitter data and VAERS. And considering robustness, input data with noises frequently occur in open-world scenarios, which presents critical challenges for the building of robust AI systems in practice. 4, Roosevelt Rd., Taipei, TaiwanAffiliation: National Taiwan UniversityPhone: +1-412-465-0130Email: yvchen@csie.ntu.edu.tw, Paul CrookAddress: 1 Hacker Way, Menlo Park, CA, USAAffiliation: FacebookPhone: +1-650-885-0094Email: pacrook@fb.com, DSTC 10 home:https://dstc10.dstc.community/homeDSTC 10 CFPs:https://dstc10.dstc.community/calls_1/call-for-workshop-papers. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. 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. KDD 2022 : 28th ACM SIGKDD Conference on Knowledge Discovery - WikiCFP The 21st Web Conference (WWW 2022), (Acceptance Rate: 17.7%), accepted. Both the research papers track and the applied data science papers track will take . IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Association for the Advancement of Artificial Intelligence, The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada. It further combines academia and industry in a quest for well-founded practical solutions. of London). All submissions must be in PDF format and formatted according to the new Standard AAAI Conference Proceedings Template. No supplement is allowed for extended abstracts. Submissions are limited to a maximum of four (4) pages, including all content and references, and must be in PDF format. 2022. It is valuable to bring together researchers and practitioners from different application domains to discuss their experiences, challenges, and opportunities to leverage cross-domain knowledge. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. You signed in with another tab or window. 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. Deadline in . AD Conference Deadlines This date takes priority over those shown below and could be extended for some programs. 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. Researchers from related fields are invited to submit papers on the recent advances, resources, tools, and upcoming challenges for SDU. Spatiotemporal Innovation Center Team. This workshop aims to bring together researchers from AI and diverse science/engineering communities to achieve the following goals: 1) Identify and understand the challenges in applying AI to specific science and engineering problems2) Develop, adapt, and refine AI tools for novel problem settings and challenges3) Community-building and education to encourage collaboration between AI researchers and domain area experts. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. PDF suitable for ArXiv repository (4 to 8 pages). The topics of interest include, but are not limited to: The papers will be presented in poster format and some will be selected for oral presentation. The workshop on Robust Artificial Intelligence System Assurance (RAISA) will focus on research, development and application of robust artificial intelligence (AI) and machine learning (ML) systems. : Papers are submitted through the CMT portal for this workshop: Please select the track for your submission in Primary Subject Area and indicate if your submission is a full paper or an extended abstract in Secondary Subject Area. See ICDM Acceptance Rates for more information. Advances in complex engineering systems such as manufacturing and materials synthesis increasingly seek artificial intelligence/machine learning (AI/ML) solutions to enhance their design, development, and production processes. Deep Learning models are at the core of research in Artificial Intelligence research today. Rex Ying's Personal Website 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. This topic also encompasses techniques that augment or alter the network as the network is trained. We consider submissions that havent been published in any peer-reviewed venue (except those under review). The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. Each accepted paper presentation will be allocated between 15 and 20 minutes. a concise checklist by Prof. Eamonn Keogh (UC Riverside). Bioinformatics (Impact Factor: 6.937), accepted, 2022. CoRL 2023 97 days 17h 29m 15s November 06-09, 2023. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. 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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