Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), pp. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. Examples of the datasets which may be considered are the DBTex Radiology Mammogram dataset and the Johns Hopkins COVID-19 case reports. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. Submitted papers will be assessed based on their novelty, technical quality, potential impact, and clarity of writing. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. LOG 2022 LOG '22 . However, you may visit "Cookie Settings" to provide a controlled consent. These submissions would benefit from additional exposure and discussion that can shape a better future publication. PDF suitable for ArXiv repository (4 to 8 pages). AI Conference Deadlines - Hyunwoo Kim Disentangled Spatiotemporal Graph Generative Model. Handwritten recognition in business documents. Recent years have witnessed growing efforts from the AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in education. Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. Important Dates. 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/. If these formalities are not completed in time, you will have to file a new application at a later date. The 2023 ACM SIGMOD/PODS Conference: Seattle, Washington, USA - Welcome iDetective: An Intelligent System for Automatic Identification of Key Actors in Online Hack Forums. The review process is double-blind, and we follow the Conflict of Interest Policy for ACM Publications. Some existing research also presents that there is a trade-off between the robustness and accuracy of deep learning models. 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. RL4ED is intended to facilitate tighter connections between researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). Each full paper will be reviewed by three PC members, while extended abstracts will not be reviewed. This AAAI workshop aims to bring together researchers from core AI/ML, robotics, sensing, cyber physical systems, agriculture engineering, plant sciences, genetics, and bioinformatics communities to facilitate the increasingly synergistic intersection of AI/ML with agriculture and food systems. Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), (Acceptance Rate: 25.6%), to appear, 2022. Guangji Bai and Liang Zhao. Consequently, standard notions of software quality and reliability such as deterministic functional correctness, black box testing, code coverage, and traditional software debugging become practically irrelevant for ML systems. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. [code] Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. ICONF 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. Integration of Deep learning and Constraint programming. 2022. The workshop aims at bridging formalisms for learning and reasoning such as neural and symbolic approaches, probabilistic programming, differentiable programming, Statistical Relation Learning and using non-differentiable optimization in deep models. All the workshop chairs, most of the Committees, and the authors of the accepted papers will attend the workshop also. Fine tuning a neural network is very time consuming and far from optimal. All the submissions must follow the AAAI-22 formatting guidelines, camera-ready style. Submit to:https://easychair.org/conferences/?conf=imlaaai22, Elizabeth DalyAddress: IBM Dublin Technology Campus, Dublin 15, IrelandEmail: elizabeth.daly@ie.ibm.com, Elizabeth Daly, IBM Research, Ireland (elizabeth.daly@ie.ibm.com), znur Alkan, IBM Research, Ireland (oalkan2@ie.ibm.com), Stefano Teso, University of Trento, Italy (stefano.teso@unitn.it), Wolfgang Stammer, TU Darmstadt, Germany (wolfgang.stammer@cs.tu-darmstadt.de), Workshop URL:https://sites.google.com/view/aaai22-imlw. PLOS ONE (impact factor: 3.534), vo. Xiaojie Guo, Yuanqi Du, Liang Zhao. This workshop starts with acknowledging the fundamental challenges of robustness and adaptiveness in financial services modeling and explores systematic solutions to solve these underlying problems to prevent future failures. We will use double-blind reviewing. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. ACM Computing Surveys (CSUR), (impact factor: 10.28), accepted. The accepted papers are allowed to be submitted to other conference venues. The post-lunch session will feature one long talk, two short talks, and a poster session. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. Explainable Agency captures the idea that AI systems will need to be trusted by human agents and, as autonomous agents themselves must be able to explain their decisions and the reasoning that produced their choices (Langley et al., 2017). SDU will be a one-day workshop. Question answering on business documents. The workshop will focus on the application of AI to problems in cyber-security. 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/. Distant-supervision of heterogeneous multitask learning for social event forecasting with multilingual indicators. 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. Self-supervised learning utilizes proxy supervised learning tasks, for example, distinguishing parts of the input signal from distractors, or generating masked input segments conditioned on the unmasked ones, to obtain training data from unlabeled corpora. Online marketplace is a digital platform that connects buyers (demand) and sellers (supply) and provides exposure opportunities that individual participants would not otherwise have access to. IEEE Transactions on Information Forensics and Security (TIFS), (impact factor: 7.178), accepted. Andrew White, University of RochesterDr. Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, Shouhuai Xu. The academic session will focus on most recent research developments on GNNs in various application domains. However, most models and AI systems are built with conservative operating environment assumptions due to regulatory compliance concerns. iCal Outlook robotics The biomedical space has seen a flurry of activity recently, and cyber criminals have amplified their efforts with health-related phishing attacks, spreading misinformation, and intruding into health infrastructure. Novel ML methods in the computational material and physical sciences. One recommended setting for Latex file is:\documentclass[sigconf, review]{acmart}. The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2022 (ACM SIGSPATIAL 2022) (Acceptance Rate: 23.8%), full paper track, to appear, 2022. . Options include pruning a trained network or training many networks automatically. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. Please note that the KDD Cup workshop will haveno proceedingsand the authors retainfull rightsto submit or post the paper at any other venue. Notable examples include the information bottleneck (IB) approach on the explanation of the generalization behavior of DNNs and the information maximization principle in visual representation learning. Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. 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. Document structure and layout learning and recognition. We will specifically invite participants of the DSTC10 tasks, track organizers, and authors of accepted papers in the general technical track. Qingzhe Li, Amir A. Fanid, Martin Slawski, Yanfang Ye, Lingfei Wu, Kai Zeng, and Liang Zhao. 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). KDD 2023 KDD '23 ​ ​ ​ August 6-10, 2023. Necessary cookies are absolutely essential for the website to function properly. Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. The positive/negative social impacts and ethical issues related to adversarial ML. "Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System." The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. Submission instructions will be available at the workshop web page. Participants will be given access to publicly available datasets and will be asked to use tools from AI and ML to generate insight from the data. The workshop follows a single-blind reviewing process. 10, pp. While original contributions are preferred, we also invite submissions of high-quality work that has recently been published in other venues or is concurrently submitted. ICDM: International Conference on Data Mining 2024 2023 2022 - WikiCFP The workshop will focus on both the theoretical and practical challenges related to the design of privacy-preserving AI systems and algorithms and will have strong multidisciplinary components, including soliciting contributions about policy, legal issues, and societal impact of privacy in AI. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. Junxiang Wang, Yuyang Gao, Andreas Zufle, Jingyuan Yang, and Liang Zhao. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. Submissions of technical papers can be up to 7 pages excluding references and appendices. The post-launch session includes the invited talks, shared task winners presentations, and a panel discussion on the resources, findings, and upcoming challenges. This workshop aims to bring together researchers from industry and academia and from different disciplines in AI and surrounding areas to explore challenges and innovations in IML. Submissions of technical papers can be up to 7 pages excluding references and appendices. and facilitate discussions and collaborations in developing trustworthy AI methods that are reliable and more acceptable to physicians. All submissions must be original contributions and will be peer reviewed, single-blinded. How can we engineer trustable AI software architectures? Time Series Clustering in Linear Time Complexity. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. job seekers, employers, recruiters and job agents. the 56th Design Automation Conference (DAC 2019), accepted, (acceptance rate: 20%), Las Vegas, US, 2019. 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 . We solicit papers describing significant and innovative research and applications to the field of job marketplaces. Submitted technical papers can be up to 4 pages long (excluding references and appendices). Kyoto . Identification of key challenges and opportunities for future research. Submissions are limited to 4 pages, not including references. Large-scale Cost-aware Classification Using Feature Computational Dependency Graph. 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. https://doi.org/10. Balaraman Ravindran (Indian Institute of Technology Madras, India ravi@cse.iitm.ac.in), Balaraman Ravindran (Indian Institute of Technology Madras, India Primary contact (ravi@cse.iitm.ac.in), Kristian Kersting (TU Darmstadt, Germany, kersting@cs.tu-darmstadt.de), Sriraam Natarajan (Univ of Texas Dallas, USA, Sriraam.Natarajan@utdallas.edu), Ginestra Bianconi (Queen Mary University of London, UK, ginestra.bianconi@gmail.com), Philip S. Chodrow (University of California, Los Angeles, USA, phil@math.ucla.edu) Tarun Kumar (Indian Institute of Technology Madras, India, tkumar@cse.iitm.ac.in), Deepak Maurya (Purdue University, India, maurya@cse.iitm.ac.in), Shreya Goyal (Indian Institute of Technology Madras, India, Goyal.3@iitj.ac.in), Workshop URL:https://sites.google.com/view/gclr2022/. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. [Best Paper Award]. We also welcome submissions that are currently under consideration in such archival venues. fact-checking. 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. 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 ). There is now a great deal of interest in finding better alternatives to this scheme. It is one of the key bottlenecks for financial services companies to improve their operating productivity. We invite submissions of full papers, as well as works-in-progress, position papers, and papers describing open problems and challenges. The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. Malicious attacks for ML models to identify their vulnerability in black-box/real-world scenarios. GraphGT: Machine Learning Datasets for Deep Graph Generation and Transformation. No supplement is allowed for extended abstracts. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 9.77%), to appear, 2022. Our goal is to build a stronger community of researchers exploring these methods, and to find synergies among these related approaches and alternatives.