By entering your email, you consent to receive communications from UdeM. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. 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. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph. 10 (2014): e110206. Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), New Orleans, US, Feb 2018, pp. Onn Shehory, Bar Ilan University (onn.shehory@biu.ac.il), Eitan Farchi, IBM Research Haifa (farchi@il.ibm.com), Guy Barash, Western Digital (Guy.Barash@wdc.com), Supplemental workshop site:https://sites.google.com/view/edsmls-2022/home. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. 3, 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. Viliam Lisy (Czech Technical University in Prague, viliam.lisy@fel.cvut.cz), Noam Brown (Facebook AI Research, noambrown@fb.com), Martin Schmid (DeepMind, mschmid@google.com), Supplemental Workshop site:http://aaai-rlg.mlanctot.info/. 8 pages), short (max. Submission URL:https://easychair.org/conferences/?conf=rl4edaaai22. Document structure and layout learning and recognition. The workshop will include original contributions on theory, methods, systems, and applications of data mining, machine learning, databases, network theory, natural language processing, knowledge representation, artificial intelligence, semantic web, and big data analytics in web-based healthcare applications, with a focus on applications in population and personalized health. convolutional neural network (CNN), recurrent neural network (RNN), etc.) No supplement is allowed for extended abstracts. 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). 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. Send this CFP to us by mail: cfp@ourglocal.org. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. Guangji Bai, Chen Ling, Liang Zhao. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. We especially welcome research from fields including but not limited to AI, human-computer interaction, human-robot interaction, cognitive science, human factors, and philosophy. 1953-1970, Oct. 2017. The academic session will focus on most recent research developments on GNNs in various application domains. Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors. We allow papers that are concurrently submitted to or currently under review at other conferences or venues. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. Fine tuning a neural network is very time consuming and far from optimal. All papers must be submitted in PDF format, using the AAAI-21 author kit and anonymized. This policy also applies to papers that overlap substantially in technical content with papers previously published, accepted, or under review. Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang. Novel ML methods in the computational material and physical sciences. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. This date takes priority over those shown below and could be extended for some programs. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". 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). Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. Papers will be peer-reviewed by the Program Committee (2-3 reviewers per paper). Despite gratifying achievements that have demonstrated the great potential and bright development prospect of introducing AI in education, developing and applying AI technologies to educational practice is fraught with its unique challenges, including, but not limited to, extreme data sparsity, lack of labeled data, and privacy issues. 2022. Data Mining Conference Acceptance Rate. ML4OR will serve as an interdisciplinary forum for researchers in both fields to discuss technical issues at this interface and present ML approaches that apply to basic OR building blocks (e.g., integer programming solvers) or specific applications. 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). Submissions that do not meet the formatting requirements will be rejected without review. Robust Regression via Online Feature Selection under Adversarial Data Corruption. We invite submissions of full papers, as well as works-in-progress, position papers, and papers describing open problems and challenges. We also invite papers that have been published at other venues to spark discussions and foster new collaborations. information bottleneck principle). 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. We hope to build upon that success. have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). Accepted papers will not be archived but will be hosted on the workshop website. The goal of ITCI22 is to bring together researchers working at the intersection of information theory, causal inference and machine learning in order to foster new collaborations and provide a venue to brainstorm new ideas, exemplify to the information theory community causal inference and discovery as an application area and highlight important technical challenges motivated by practical ML problems, draw the attention of the wider machine learning community to the problems at the intersection of causal inference and information theory, and demonstrate to the community the utility of information-theoretic tools to tackle causal ML problems.