ADMM for Efficient Deep Learning with Global Convergence. All these changes require novel solutions, and the AI community is well-positioned to provide both theoretical- and application-based methods and frameworks. Necessary cookies are absolutely essential for the website to function properly. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. The workshop will include several technical sessions, a virtual poster session where presenters can discuss their work, to further foster collaborations, multiple invited speakers covering crucial aspects for the practical deep learning in the wild, especially the efficient and robust deep learning, some tutorial talks, the challenge for efficient deep learning and solution presentations, and will conclude with a panel discussion. Half day event featuring a panel, invited and keynote speakers and presentations selected through a CFP. It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 14.255), accepted. 2022. The acceptance decisions will take in account novelty, technical depth and quality, insightfulness, depth, elegance, practical or theoretical impact, reproducibility and presentation. Exploring the limits of self-supervised learning approaches for speech and audio processing, for example, adverse environment conditions, multiple languages, or generalization across downstream tasks. The theme of the hack-a-thon will be decided before submission is closed and will be focused around finding creative solutions to novel problems in health. Can AI achieve the same goal without much low-level supervision? May 8, 2022: Student Travel Awards announcement is, Apr. We encourage authors to contact the organizers to discuss possible overlap. 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. New self-supervised proxy tasks or new approaches using self-supervised models in speech and audio processing. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. Submissions will be peer reviewed, single-blinded. Xiaojie Guo, Yuanqi Du, Liang Zhao. "Robust Regression via Heuristic Hard Thresholding". InProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2013), demo track, pp. In recent years, various information theoretic principles have also been applied to different deep learning related AI applications in fruitful and unorthodox ways. KDD 2022 : Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. 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. Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad. 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. We consider submissions that havent been published in any peer-reviewed venue (except those under review). RES: A Robust Framework for Guiding Visual Explanation. Both the research papers track and the applied data science papers track will take . Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. Attendance is open to all registered participants. Connor Coley, Massachusetts Institute of TechnologyProf. Submission URL:https://easychair.org/my/conference?conf=vtuaaai2022. Submissions are limited to a total of 5 pages for initial submission (up to 6 pages for final camera-ready submission), excluding references or supplementary materials, and authors should only rely on the supplementary material to include minor details that do not fit in the 5 pages. Like other systems, ML systems must meet quality requirements. How to do good research, Get it published in SIGKDD and get it cited! The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. 11-13. This topic encompasses forms of Neural Architecture Search (NAS) in which the performance properties of each architecture, after some training, are used to guide the selection of the next architecture to be tried. Check the deadlines for submitting your application. "Misinformation Propagation in the Age of Twitter." 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. The accepted papers are allowed to be submitted to other conference venues. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. Computer Science and Engineering, INESC-ID, IST Ulisboa, Lisbon, Portugal currently at Sorbonne University, Paris, France silvia.tulli@gaips.inesc-id.pt), Prashan Madumal (Science and Information Systems, University of Melbourne, Parkville, Australia pmathugama@student.unimelb.edu.au), Mark T. Keane (School of Computer Science, University College Dublin, Dublin, Ireland mark.keane@ucd.ie), David W. Aha (Navy Center for Applied Research in AI, Naval Research Laboratory, Washington, DC, USA david.aha@nrl.navy.mil), Adam Johns (Drexel University, Philadelphia, PA USA), Tathagata Chakraborti (IBM Research AI, Cambridge, MA USA), Kim Baraka (VU University Amsterdam, Netherlands), Isaac Lage (Harvard University, Cambridge, MA USA), David Martens (University of Antwerp, Belgium), Mohamed Chetouani (Sorbonne Universit, Paris, France), Peter Flach (University of Bristol, United Kingdom), Kacper Sokol (University of Bristol, United Kingdom), Ofra Amir (Technion, Haifa, Israel), Dimitrios Letsios (Kings College London, London, United Kingdom), Supplemental workshop site:https://sites.google.com/view/eaai-ws-2022/topic. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. 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. ISPRS International Journal of Geo-Information (IJGI), (impact factor: 1.502), 5.10 (2016): 193. Oct. 24, 2021: The KDD2022 website is LIVE! 2022. Some specific topics in the context of scientific discovery and engineering design include (but not limited to): This will be a one day workshop with a number of paper presentations and poster spotlights, a poster session, several invited talks, and a panel discussion. What approaches emerge in building fundamentally robust and adaptive AI/ML systems? "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Saliency-regularized Deep Multi-task Learning. 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. DB transactions) to unstructured data (e.g. Additionally, adversaries continue to develop new attacks. Qingzhe Li, Jessica Lin, Liang Zhao and Huzefa Rangwala. Papers will be peer-reviewed and selected for spotlight and/or poster presentation at the workshop. 25, 2022: We have announced Call for Nominations: , Mar. The automated processing of unstructured data to discover knowledge from complex financial documents requires a series of techniques such as linguistic processing, semantic analysis, and knowledge representation & reasoning. Temporal Domain Generalization with Drift-Aware Dynamic Neural Network. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. 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/. : 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. Attendance is open to all. Information extraction from text and semi-structured documents. Deep learning and statistical methods for data mining. 2020. The AAAI-22 workshop program includes 39 workshops covering a [] Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Novel mechanisms for eliciting and consuming user feedback, recommender, structured and generative models, concept acquisition, data processing, optimization; HCI and visualization challenges; Analysis of human factors/cognition and user modelling; Design, testing and assessment of IML systems; Studies on risks of interaction mechanisms, e.g., information leakage and bias; Business use cases and applications. The goal of this workshop is to offer an opportunity to appreciate the diversity in applications, to draw connections to inform decision optimization across different industries, and to discover new problems that are fundamental to marketplaces of different domains. Accepted papers will be given the opportunity to present at the spotlight sessions during the workshop. 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. 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. Moreover, to tackle and overcome several issues in personalized healthcare, information technology will need to evolve to improve communication, collaboration, and teamwork among patients, their families, healthcare communities, and care teams involving practitioners from different fields and specialties. This workshop aims to bring together researchers and practitioners working on different facets of these problems, from diverse backgrounds to share challenges, new directions, recent research results, and lessons from applications. The first AAAI Workshop on AI for Design and Manufacturing, ADAM, aims to bring together researchers from core AI/ML, design, manufacturing, scientific computing, and geometric modeling. The workshop attracted about 100 attendees. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. Proposals of technical talk (up to one-page abstract including short Bio of the main speaker). Motif-guided Heterogeneous Graph Deep Generation. Liang Zhao, Feng Chen, and Yanfang Ye. 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. BERT and GPT in NLP and SimCLR and BYOL in CV are famous examples in this direction. In this workshop we would like to focus on a contrasting approach, to learn the architecture during training. Yuanqi Du, Xiaojie Guo, Yinkai Wang, Amarda Shehu, Liang Zhao. robust and interpretable natural language processing for healthcare. 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. 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. Scientific documents such as research papers, patents, books, or technical reports are one of the most valuable resources of human knowledge. 29, no. Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad,. in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. We would especially like to highlight approaches that are qualitatively different from some popular but computationally intensive NAS methods. AAAI is pleased to present the AAAI-22 Workshop Program. Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, Girish Chowdhary (University of Illinois, Urbana Champaign), Baskar Ganapathysubramanian (Iowa State University; contact: baskarg@iastate.edu), George Kantor (Carnegie Mellon University), Soumyashree Kar (Iowa State University), Koushik Nagasubramanian (Iowa State University), Soumik Sarkar (Iowa State University), Katia Sycara (Carnegie Mellon University), Sierra Young (North Carolina State University), Alina Zare (University of Florida, Gainesville), Supplemental workshop site:https://aiafs-aaai2022.github.io/. While we are planning an in-person workshop to be held at AAAI-22, we aim to accommodate attendees who may not be able to travel to Vancouver by allowing participation via live virtual invited talks and virtual poster sessions. Meta-learning models from various existing task-specific AI models. Information theory has demonstrated great potential to solve the above challenges. The cookie is used to store the user consent for the cookies in the category "Analytics". 2022. Deep Graph Spectral Evolution Networks for Graph Topological Evolution. Xiaojie Guo and Liang Zhao. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. Please use ACM Conference templates (two column format). Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Fanny Ye, Chang-tien Lu, and Naren Ramakrishnan. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features. Programming Languages, Domain specific languages, Libraries and software tools for integration of various learning and reasoning paradigms. Ourprevious workshop at AAAI-21generated significant interest from the community. ICLR 2022 Meeting Dates The Tenth annual conference is held Mon. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. System reports should also follow the AAAI 2022 formatting guidelines and have 4-6 pages including references. Registration Opens: Feb 02 '22 02:00 PM UTC: Registration Cancellation Refund Deadline: Apr 18 '22(Anywhere on Earth) Paper Submissions Abstract Submission Deadline: Sep 29 '21 12:00 AM UTC: Paper Submission deadline: Oct 06 '21 12:00 AM . These submissions would benefit from additional exposure and discussion that can shape a better future publication. We aim to bring together researchers in AI, healthcare, medicine, NLP, social science, etc. The PAKDD is one of the longest established and leading international conferences in the areas of data mining and knowledge discovery. 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. And with particular focuses but not limited to these application domains: Our program consists of two sessions: academic session and industry session. 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. While there have been extensive independent research threads on the subject of safety and reliability of specific sub-problems in autonomy, such as the problem of robust control, as well as recent considerations of robust AI-based perception, there has been considerably less research on investigating robustness and trust in end-to-end autonomy, where AI-based perception is integrated with planning and control in an open loop. Participants in the hack-a-thon will be asked to either register as a team or be randomly assigned to a team after registration. 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 audience of this workshop will be researchers and students from a wide array of disciplines including, but not limited to, statistics, computer science, economics, public policy, psychology, management, and decision science, who work at the intersection of causal inference, machine learning, and behavior science. First, large data sources, both conventionally used in social sciences (EHRs, health claims, credit card use, college attendance records) and unconventional (social networks, fitness apps), are now available, and are increasingly used to personalize interventions. Contrast Pattern Mining in Paired Multivariate Time Series of Controlled Driving Behavior Experiment. We welcome full research papers, position papers, and extended abstracts. Well also host a competition on adversarial ML along with this workshop. Accepted submissions will have the option of being posted online on the workshop website. The advances in web science and technology for data management, integration, mining, classification, filtering, and visualization has given rise to a variety of applications representing real-time data on epidemics. the 33rd Annual Computer Security Applications Conference (ACSAC 2018), (acceptance rate: 20.1%), San Juan, Puerto Rico, USA, Dec 2018, accepted. The main objective of the workshop is to bring researchers together to discuss ideas, preliminary results, and ongoing research in the field of reinforcement in games. Ting Hua, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Attendance is open to all registered participants. Please note that the KDD Cup workshop will haveno proceedingsand the authors retainfull rightsto submit or post the paper at any other venue. Atlanta, Georgia, USA . Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. Chen Ling, Carl Yang, and Liang Zhao. "Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning." The desired LENGTH of the workshop: Full-day (~8 hours). Analytical cookies are used to understand how visitors interact with the website. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022.
Glidden Funeral Home Obituaries, Weld County Jail Mugshots, Delaware North Executives, Medical Futility Laws By State, Articles K
Glidden Funeral Home Obituaries, Weld County Jail Mugshots, Delaware North Executives, Medical Futility Laws By State, Articles K