The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), (Acceptance Rate: 25.6%), to appear, 2022. [paper] Abstracts of the following flavors will be sought: (1) research ideas, (2) case studies (or deployed projects), (3) review papers, (4) best practice papers, and (5) lessons learned. and deep learning techniques (e.g. Zero Speech challenge is to build language models only based on audio or audio-visual information, without using any textual input. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. Invited speakers, committee members, authors of the research paper, and the participants of the shared task are invited to attend. Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/ADAM, Aarti Singh (Carnegie Mellon University), Baskar Ganapathysubramanian (ISU), Chinmay Hegde (New York University; contact: chinmay.h@nyu.edu), Mark Fuge (University of Maryland), Olga Wodo (University of Buffalo), Payel Das (IBM), Soumalya Sarkar (Raytheon), Workshop website:https://adam-aaai2022.github.io/. Algorithms for secure and privacy-aware machine learning for AI. We aim to bring together researchers in AI, healthcare, medicine, NLP, social science, etc. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. 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. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. ), 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). It is one of the key bottlenecks for financial services companies to improve their operating productivity. The submission website ishttps://cmt3.research.microsoft.com/OTSDM2022. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. Extracting knowledge or insights from this abundance of data lies at the heart of 21st century discovery, which can be used to inform decisions, coordinate activities, optimize processes, improve products and services, as well as enhance productivity and innovation across a wide range of business and scientific problems. This website uses cookies to improve your experience while you navigate through the website. Accelerated Gradient-free Neural Network Training by Multi-convex Alternating Optimization. 17th International Workshop on Mining and Learning with Graphs. Autonomous vehicles can share their detected information (e.g., traffic signs, collision events, etc.) We invite the submission of papers with 4-6 pages. The current research in this area is focused on extending existing ML algorithms as well as network science measures to these complex structures. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. We welcome submissions of long (max. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. Washington DC, USA. Scientists and engineers in diverse domains are increasingly relying on using AI tools to accelerate scientific discovery and engineering design. The submissions must follow the formatting guidelines for AAAI-22. Generative Deep Learning for Macromolecular Structure and Dynamics, Current Opinion in Structural Biology, (impact factor: 7.108), Section on Theory and Simulation/Computational Methods 67: 170-177, 2021 accepted. "Multi-Task Learning for Spatio-Temporal Event Forecasting." We also use third-party cookies that help us analyze and understand how you use this website. 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. Previously published work (or under-review) is acceptable. Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Moreover, the operational context in which AI systems are deployed necessitates consideration of robustness and its relation to principles of fairness, privacy, and explainability. The submission website ishttps://cmt3.research.microsoft.com/PracticalDL2022. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. In this workshop, we want to explore ways to bridge short-term with long-term issues, idealistic with pragmatic solutions, operational with policy issues, and industry with academia, to build, evaluate, deploy, operate and maintain AI-based systems that are demonstrably safe. Unsupervised Deep Subgraph Anomaly Detection. The workshop will focus on the application of AI to problems in cyber-security. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. "Controllable Data Generation by Deep Learning: A Review." Mingxuan Ju, Wei Song, Shiyu Sun, Yanfang Ye, Yujie Fan, Shifu Hou, Kenneth Loparo, and Liang Zhao. Publication in HC-SSL does not prohibit authors from publishing their papers in archival venues such as NeurIPS/ICLR/ICML or IEEE/ACM Conferences and Journals.
Iclr 2022 These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. We will include a panel discussion to close the workshop, in which the audience can ask follow up questions and to identify the key AI challenges to push the frontiers in Chemistry.
Funeral for Nadine Girault will take place Saturday | CTV News 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 . Attendance is open to all; at least one author of each accepted paper must be virtually present at the workshop. Extended abstract up to 2 pages are also welcome. Big data Journal (impact factor: 1.489), vo. 4498-4505, New Orleans, US, Feb 2018. 25-50 attendees including invited speakers and accepted papers. convolutional neural network (CNN), recurrent neural network (RNN), etc.) We expect 50~75 participants and potentially more according to our past experiences. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. Given the ever-increasing role of the World Wide Web as a source of information in many domains including healthcare, accessing, managing, and analyzing its content has brought new opportunities and challenges. 2020. This cookie is set by GDPR Cookie Consent plugin. At least one author of each accepted submission must be present at the workshop. The Conference. Make sure your desired study programs are open for admission in the session when you would like to start your studies. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. The desired LENGTH of the workshop: Full-day (~8 hours). Submission Site: See the webpagehttps://sites.google.com/view/gclr2022/submissions; for detailed instructions and submission link. Multilingual document understanding methods and frameworks. ACM, 2013. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Dazhou Yu, Guangji Bai, Yun Li, and Liang Zhao. Integration of non-differentiable optimization models in learning.
and Simone Stumpf (Univ. Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. Han Wang, Hossein Sayadi, Avesta Sasan, Houman Homayoun, Liang Zhao, Tinoosh Mohsenin, Setareh Rafatirad. Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. Workshops are one day unless otherwise noted in the individual descriptions. Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Jiabin Wang, and Qi Xiong. Conference stats are visualized below for a straightforward comparison. "GA-based principal component selection for production performance estimation in mineral processing." a fantastic tutorial on SIGKDD'09 by Prof. Eamonn Keogh (UC Riverside). in Proceedings of the SIAM International Conference on Data Mining (SDM 2015), (acceptance rate: 22%), Vancouver, BC, pp. Submission at:https://easychair.org/my/conference?conf=edsmls2022. Interpreting and Evaluating Neural Network Robustness. The goal of the inaugural HC-SSL workshop is to highlight and facilitate discussions in this area and expose the attendees to emerging potentials of SSL for human-centric representation learning, and promote responsible AI within the context of SSL. It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. KDD 2022 | Washington DC, U.S. SIGKDD CONFERENCE Latest News Aug 12, 2022: Please check out the proceedings access information. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. Novel AI-based techniques to improve modeling of engineering systems. We invite paper submission on the following (and related) topics: The workshop will be a 1 day meeting comprising several invited talks from distinguished researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work, and a concluding panel discussion focusing on future directions. Public health authorities and researchers collect data from many sources and analyze these data together to estimate the incidence and prevalence of different health conditions, as well as related risk factors. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. We welcome full paper submissions (up to 8 pages, excluding references or supplementary materials). How to do good research, Get it published in SIGKDD and get it cited! Liang Zhao, Olga Gkountouna, and Dieter Pfoser.
ICONF Spatial Event Forecasting in Social Media with Geographically Hierarchical Regularization. All papers will be peer reviewed, single-blinded. December 2020, July 21: Clarified that the workshop this year will be held, June 20: Paper notification is now extended to, Paper reviews are underway!
ICDM: International Conference on Data Mining 2024 2023 2022 - WikiCFP The workshop page ishttps://sites.google.com/view/aaaiwfs2022, and it will include the most up-to-date information, including the exact schedule. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. NOTE: Mandatory abstract deadline on Oct 13, 2022. Finally, there is an increasing interest in AI in moving beyond traditional supervised learning approaches towards learning causal models, which can support the identification of targeted behavioral interventions. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. .
This thread already has a best answer. [slides] In recent years, various information theoretic principles have also been applied to different deep learning related AI applications in fruitful and unorthodox ways. In addition, authors can provide an optional one page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. Lastly, learning joint modalities is of interest to both Natural Language Processing (NLP) and Computer Vision (CV) forums. The workshop combines several disciplines, including ML, software engineering (with emphasis on quality), security, and game theory. ASPLOS 2023 will be moving to three submission deadlines. However, the performance and efficiency of these techniques are big challenges for performing real-time applications. Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. August 14-18, 2022. Malicious attacks for ML models to identify their vulnerability in black-box/real-world scenarios. Please note that the KDD Cup workshop will have no proceedings and the authors retain full rights to submit or post the paper at any other venue. Attendance is open to all registered participants. ETA (expected time-of-arrival) prediction. Previous healthcare-related workshops focus on how to develop AI methods to improve the accuracy and efficiency of clinical decision-making, including diagnosis, treatment, triage. It will start with a 60-minute mini-tutorial covering the basics of RL in games, and will include 2-4 invited talks by prominent contributors to the field, paper presentations, a poster session, and will close with a discussion panel. Atlanta, Georgia, USA . Online and Distributed Robust Regressions with Extremely
Noisy Labels. The program of the workshop will include invited talks, paper presentations and a panel discussion. 15, pp. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. 2020. 2022. Despite the great success of deep neural networks (DNNs) in many artificial intelligence (AI) tasks, they still suffer from limitations, such as poor generalization behavior for out-of-distribution (OOD) data, vulnerability to adversarial examples, and the black-box nature of DNNs. We expect ~60 attendees. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. In Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. Neural Networks, (impact factor: 8.05), accepted. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. GNES: Learning to Explain Graph Neural Networks. 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 is the premier Data Science conference.
Oilers Outperform Division Rivals at 2023 Trade Deadline in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. Liang Zhao, Ting Hua, Chang-Tien Lu, and Ing-Ray Chen. It further combines academia and industry in a quest for well-founded practical solutions. KDD 2022 : Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. information bottleneck principle). The reproducibility papers include a clarification phase: Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Yuyang Gao, Giorgio Ascoli, Liang Zhao. Both the research papers track and the applied data science papers track will take . Optimal transport theory, including statistical and geometric aspects; Gromov-Wasserstein distance and its variants; Bayesian inference for/with optimal transport; Gromovization of machine learning methods; Optimal transport-based generative modeling. All submissions must be anonymous and conform to AAAI standards for double-blind review. 639-648, Nov 2015. How can we engineer trustable AI software architectures? [Best Paper Award Shortlist]. ISPRS International Journal of Geo-Information (IJGI), (impact factor: 1.502), 5.10 (2016): 193. Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting. The submission website ishttps://cmt3.research.microsoft.com/TAIH2022. Deep learning has achieved significant success for artificial intelligence (AI) in multiple fields. The workshop will be co-located with the KDD 2022 conference at Washington DC Convention Center,Washington D.C., USA onAugust 17th, 2022 at1PM5PM (Eastern Standard Time). Scott E. Fahlman, School of Computer Science, Carnegie Mellon University (sef@cs.cmu.edu), Edouard Oyallon, Sorbonne Universit LIP6 (Edouard.oyallon@lip6.fr), Dean Alderucci, School of Computer Science, Carnegie Mellon University, (dalderuc@cs.cmu.edu). Journal of Biomedical Semantics, (impact factor: 1.845), 2018, accepted. We will accept both original papers up to 8 pages in length (including references) as well as position papers and papers covering work in progress up to 4 pages in length (not including references).Submission will be through Easychair at the AAAI-22 Workshop AI4DO submission site, Professor Bistra Dilkina (dilkina@usc.edu), USC and Dr. Segev Wasserkrug, (segevw@il.ibm.com), IBM Research, Prof. Andrea Lodi (andrea.lodi@cornell.edu), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (dharmash@us.ibm.com), IBM Research. Despite rapid recent progress, it has proven to be challenging for Artificial Intelligence (AI) algorithms to be integrated into real-world applications such as autonomous vehicles, industrial robotics, and healthcare. An example of the latter is theCascade Correlation algorithm, as well as others that incrementally build or modify a neural network during training, as needed for the problem at hand. 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. 10, pp. We received 38 paper submissions and accepted 23 of them. The workshop is being organized by application area or other, panels, invited speakers, interactive, small groups, discussions, presentations.
KDD 2022 -ACM SIGKDD International Conference on Knowledge Discovery 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. By entering your email, you consent to receive communications from UdeM. Proceedings of the IEEE (impact factor: 9.237), vol. Accepted papers are likely to be archived. Hence, this workshop will focus on introducing research progress on applying AI to education and discussing recent advances of handling challenges encountered in AI educational practice. job seekers, employers, recruiters and job agents. The workshop is a full day. We will specifically invite participants of the DSTC10 tasks, track organizers, and authors of accepted papers in the general technical track. Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu. The last few years have seen the rapid development of mathematical methods for modeling structured data coming from biology, chemistry, network science, natural language processing, and computer vision applications. We will also select some of the best posters for spotlight talks (2 minutes each). ADMM for Efficient Deep Learning with Global Convergence. Information extraction from text and semi-structured documents. Hua, Ting, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Short papers 10m presentation and 5m discussion. San Francisco, USA . "STED: semi-supervised targeted-interest event detectionin in twitter." Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. 2022. The accepted papers are allowed to be submitted to other conference venues. 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. Deep learning and statistical methods for data mining. 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. in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. Submissions must be formatted in the AAAI submission format (https://www.aaai.org/Publications/Templates/AuthorKit22.zip) All submissions should be done electronically via EasyChair. Well also host a competition on adversarial ML along with this workshop. An Invertible Graph Diffusion Model for Source Localization. International Journal of Digital Earth, (impact factor: 3.097), 25 Aug 2020, https://doi.org/10.1080/17538947.2020.1809723. SDU will be a one-day workshop. With the rapid development of advanced techniques on the intersection between information theory and machine learning, such as neural network-based or matrix-based mutual information estimator, tighter generalization bounds by information theory, deep generative models and causal representation learning, information theoretic methods can provide new perspectives and methods to deep learning on the central issues of generalization, robustness, explainability, and offer new solutions to different deep learning related AI applications.This workshop aims to bring together both academic researchers and industrial practitioners to share visions on the intersection between information theory and deep learning, and their practical usages in different AI applications.