Knowledge Discovery and Data Mining. The accepted papers are allowed to be submitted to other conference venues. In this workshop we would like to focus on a contrasting approach, to learn the architecture during training. Such advances would enrich the range of applicability of semi-autonomous systems to real-world tasks, most of which involve cooperation with one or more human partners. 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. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. 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. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. We also use third-party cookies that help us analyze and understand how you use this website. 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. July 22: The workshop Programis up! Precision agriculture and farm management, Development of open-source software, libraries, annotation tools, or benchmark datasets, Bias/equity in algorithmic decision-making, AI for ITS time-series and spatio-temporal data analyses, AI for the applications of transportation, Applications and techniques in image recognition based on AI techniques for ITS, Applications and techniques in autonomous cars and ships based on AI techniques. Welcome to the home of the 2023 ACM SIGMOD/PODS Conference, to be held in the Seattle metropolitan area, Washington, USA, on June 18 - June 23, 2023. All papers must be submitted in PDF format, using the AAAI-22 author kit. Attendance is open to all registered participants. "Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework",The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. arXiv preprint arXiv:2002.11867 (2021), Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao. Previously published work (or under-review) is acceptable. All submissions will be peer-reviewed. Chen Ling, Hengning Cao, Liang Zhao. In recent years, we have seen examples of general approaches that learn to play these games via self-play reinforcement learning (RL), as first demonstrated in Backgammon. 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. We encourage long papers, short papers and demo papers. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. 25-50 attendees including invited speakers and accepted papers. Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. 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. What safety engineering considerations are required to develop safe human-machine interaction? ICLR 2022 Meeting Dates The Tenth annual conference is held Mon. "Robust Regression via Heuristic Hard Thresholding". Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. Knowledge Discovery and Data Mining is an interdisciplinary area focusing upon methodologies and applications for extracting useful knowledge from data [1] . Business documents are central to the operation of all organizations, and they come in all shapes and sizes: project reports, planning documents, technical specifications, financial statements, meeting minutes, legal agreements, contracts, resumes, purchase orders, invoices, and many more. The role of adjacent fields of study (e.g, computational social science) in mitigating issues of bias and trust in AI. 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. Submissions tackling new problems or more than one of the aforementioned topics simultaneously are encouraged. Well also host a competition on adversarial ML along with this workshop. Time Series Clustering in Linear Time Complexity. Make sure your desired study programs are open for admission in the session when you would like to start your studies. 2022. We will also organize 3 shared tasks in this workshop: punctuation restoration, domain adaptation for punctuation restoration, and chitchat detection. Because of the time needed to complete the formalities for entering Canada and Quebec, the admission period for international applicants ends several weeks before the session begins. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. 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. This workshop brings together researchers from diverse backgrounds with different perspectives to discuss languages, formalisms and representations that are appropriate for combining learning and reasoning. In other words, many existing FL solutions are still exposed to various security and privacy threats. 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). The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. Integrated syntax and semantic approaches for document understanding. Lyle Unga (University of Pennsylvania, [email protected]), Rahul Ladhania* (University of Michigan, [email protected], primary contact), Linnea Gandhi (University of Pennsylvania, [email protected]), Michael Sobolev (Cornell Tech, [email protected]), Supplemental workshop site:https://ai4bc.github.io/ai4bc22/, For any questions, please reach out to us at ai4behaviorchange at gmail dot com. References will not count towards the page limit. These complex demands have brought profound implications and an explosion of interest for research into the topic of this workshop, namely building practical AI with efficient and robust deep learning models. Proceedings of the IEEE (impact factor: 9.237), vol. All papers will be peer reviewed, single-blinded. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). To facilitate KDD related research, we create this repository with: *ICDM has two tracks (regular paper track and short paper track), but the exact statistic is not released, e.g., the split between these two tracks. Integration of neuro and symbolic approaches. Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior. Like other systems, ML systems must meet quality requirements. What approaches emerge in building fundamentally robust and adaptive AI/ML systems? Your Style Your Identity: LeveragingWriting and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network, The Web Conference (WWW 2019), short paper, (acceptance rate: 20%), accepted, 2019. GNES: Learning to Explain Graph Neural Networks. The 39th IEEE International Conference on Data Engineering (ICDE 2023), accepted. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. 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. Event Prediction in the Big Data Era: A Systematic Survey. algorithms applied to the above topics: deep learning, reinforcement learning, multi-armed bandits, causal inference, mathematical programming, and stochastic optimization. It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. Submission URL:https://easychair.org/conferences/?conf=rl4edaaai22. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. Integration of probabilistic inference in training deep models. There were two workshops on similar topics hosted at ICML 2020 and NeurIPS 2020, and both workshops observed positive feedback and overwhelming participation. We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. Dynamic Tracking and Relative Ranking of Airport Threats from News and Social Media. iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. Junxiang Wang, Fuxun Yu, Xiang Chen, and Liang Zhao. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. For further information, please have a look at the call for contributions. We invite novel contributions following the AAAI-22 formatting guidelines, camera-ready style. Cesa Salaam (Howard University, USA), Hwanhee Lee (Seoul National University, South Korea), Jaemin Cho (University of North Carolina at Chapel Hill, USA), Jielin Qiu (Carnegie Mellon University, USA), Joseph Barrow (University of Maryland, US), Mengnan Du (Texas A&M University, USA), Minh Van Nguyen (University of Oregon, USA), Nicole Meister (Princeton University, USA), Sajad Sotudeh Gharebagh (Georgetown University, USA), Sampreeth Chebolu (University of Houston, USA), Sarthak Jain (Northeastern University, USA),Shufan Wang (University of Massachusetts Amherst, USA), Supplemental Workshop site:https://vtuworkshop.github.io/2022/, https://research.ibm.com/haifa/Workshops/AAAI-22-AI4DO/. Liang Zhao, Junxiang Wang, and Xiaojie Guo. Xiaojie Guo, Lingfei Wu, Liang Zhao. iCal Outlook robotics IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. DB transactions) to unstructured data (e.g. Distant-supervision of heterogeneous multitask learning for social event forecasting with multilingual indicators. In our workshop, we specifically focus on the trustworthy issues in AI for healthcare, aiming to make clinical AI methods more reliable in real clinical settings and be willingly used by physicians. Attendance is open to all prior registration to the workshop/conference. The robust development and assured deployment of AI systems: Participants will discuss how to leverage and update common software development paradigms, e.g., DevSecOps, to incorporate relevant aspects of system-level AI assurance. We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. 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. Feng Chen, Baojian Zhou, Adil Alim, Liang Zhao. in Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), research track, (acceptance rate: 19.4%), Sydney, Australia, pp. It is important to learn how to use AI effectively in these areas in order to be able to motivate and help people to take actions that maximize their welfare. Some examples of the success of information theory in causal inference are: the use of directed information, minimum entropy couplings and common entropy for bivariate causal discovery; the use of the information bottleneck principle with applications in the generalization of machine learning models; analyzing causal structures of deep neural networks with information theory; among others. Interpretable Molecular Graph Generation via Monotonic Constraints. 2022. The availability of massive amounts of data, coupled with high-performance cloud computing platforms, has driven significant progress in artificial intelligence and, in particular, machine learning and optimization. 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. Meta-learning models from various existing task-specific AI models. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. 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. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), (acceptance rate: 16.8%), August 23-27, 2020, Virtual Event, CA, USA. 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). 1953-1970, Oct. 2017. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. Attendance is open to all. the 33rd Annual Computer Security Applications Conference (ACSAC 2018), (acceptance rate: 20.1%), San Juan, Puerto Rico, USA, Dec 2018, accepted. The VTU workshops accepts both short paper (4 pages) and long paper (8 pages). These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. The current research in this area is focused on extending existing ML algorithms as well as network science measures to these complex structures. 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. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. of Graz), Cynthia Rudin (Duke Univ.) The submission website ishttps://cmt3.research.microsoft.com/OTSDM2022. 7, no. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. Following this AAAI conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. (Depending on the volume of submissions, we may be able to accommodate only a subset of them.). 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. [slides] Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Fanny Ye, Chang-tien Lu, and Naren Ramakrishnan. 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. December, 12-16, 2022. iDetective: An Intelligent System for Automatic Identification of Key Actors in Online Hack Forums. arXiv preprint arXiv:2302.02093 (2023). Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. 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. 10, pp. 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. This half day workshop will focus on research into the use of AI techniques to extract knowledge from unstructured data in financial services. Oral presentations: 10 minute presentation for oral papers. Deep Learning models are at the core of research in Artificial Intelligence research today. 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. SDU will be a one-day workshop. We will accept the extended abstracts of the relevant and recently published work too. Table identification and extraction from business documents. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. Shiyu Wang, Xiaojie Guo, Liang Zhao. : 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. Pengtao Xie (main contact), Assistant Professor, University of California, San Diego, [email protected] Engineer Ln, San Diego, CA 92161 (Tel)4123206230, Marinka Zitnik, Assistant Professor, Harvard University, [email protected] 10 Shattuck Street, Boston, MA 02115 (Tel)6503086763, Byron Wallace, Assistant Professor, Northeastern University, [email protected] 177 Huntington Ave, Boston, MA 02115 (Tel)4135120352, Eric P. Xing, Professor, Carnegie Mellon University, [email protected] 5000 Forbes Ave, Pittsburgh, PA 15213 (Tel)4122682559, Ramtin Hosseini, PhD Student, University of California, San Diego, [email protected] (Tel) 3104293825, Ethics and fairness in autonomous systems, Robust robotic design, particularly of autonomous drones and/or vehicles. . RES: A Robust Framework for Guiding Visual Explanation. Topics of interest include but are not limited to: (1) Survey papers summarizing recent advances in RL with applicability to ED; (2) Developing toolkits and datasets for applying RL methods to ED; (3) Using RL for online evaluation and A/B testing of different intervention strategies in ED; (4) Novel applications of RL for ED problem settings; (5) Using pedagogical theories to narrow the policy space of RL methods; (6) Using RL methodology as a computational model of students in open-ended domains; (7) Developing novel offline RL methods that can efficiently leverage historical student data; (8) Combining statistical power of RL with symbolic reasoning to ensure the robustness for ED. Deep Graph Translation. 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. At the AAAI 2022 Workshop on Video Transcript Understanding (VTU @ AAAI 2022), we aim to bring together researchers from various domains to make the best of the knowledge that all these videos contain. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. Viliam Lisy (Czech Technical University in Prague, [email protected]), Noam Brown (Facebook AI Research, [email protected]), Martin Schmid (DeepMind, [email protected]), Supplemental Workshop site:http://aaai-rlg.mlanctot.info/. "A Uniform Representation for Trajectory Learning Tasks", 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2017), short paper, DOI=10.1145/3139958.3140017, Redondo Beach, CA, USA, Nov 2017. 25, 2022: We have announced Call for Nominations: , Mar.

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