Comparison or integration of self-supervised learning methods and other semi-supervised and transfer learning methods in speech and audio processing tasks. 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. 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 are due by 12 November 2021. Researchers from related domains are invited to submit papers on recent advanced technologies, resources, tools and challenges for VTU. It is anticipated that this will be an in-person workshop, subject to changing travel restrictions and health measures. In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. However, FL also faces multiple challenges that may potentially limit its applications in real-world use scenarios. The submissions need to be anonymized. If the admission deadline for international applicants is past, we suggest that you choose another session to begin your studies. Algorithms for secure and privacy-aware machine learning for AI. Oilers Outperform Division Rivals at 2023 Trade Deadline Finally, the workshop will welcome papers that describe the release of privacy-preserving benchmarks and data sets that can be used by the community to solve fundamental problems of interest, including in machine learning and optimization for health systems and urban networks, to mention but a few examples. Panel discussion: Interactive Q&A session with a panel of leading researchers. Checklist for Revising a SIGKDD Data Mining Paper, How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering, https://researcher.watson.ibm.com/researcher/view_group.php?id=144, IEEE International Conference on Big Data (, AAAI Conference on Artificial Intelligence (, IEEE International Conference on Data Engineering (, SIAM International Conference on Data Mining (, Pacific-Asia Conference on Knowledge Discovery and Data Mining (, ACM SIGKDD International Conference on Knowledge discovery and data mining (, European Conference on Machine learning and knowledge discovery in databases (, ACM International Conference on Information and Knowledge Management (, IEEE International Conference on Data Mining (, ACM International Conference on Web Search and Data Mining (, 18.4% (181/983, research track), 22.5% (112/497, applied data science track), 59.1% (107/181, research track), 35.7% (40/112, applied data science track), 17.4% (130/748, research track), 22.0% (86/390, applied data science track), 49.2% (64/130, research track), 41.9% (36/86, applied data science track), 18.1% (142/784, research track), 19.9% (66/331, applied data science track), 49.3% (70/142, research track), 60.1% (40/66, applied data science track), 18.5% (194/1046, overall), 9.1% (95/?, regular paper), ?% (99/?, short paper), 19.8% (188/948, overall), 8.9% (84/?, regular paper), ?% (104/?, short paper), 19.9% (155/778, overall), 9.3% (72/?, regular paper), ?% (83/?, short paper), 19.6% (178/904, overall), 8.6% (78/?, regular paper), ?% (100/?, short paper), 19.6% (202/1031, long paper), 22.7% (107/471, short paper), 21.8% (38/174m applied research), 17% (147/826, long paper), 23% (96/413, short paper), 25% (demo), 34% (industry paper), Short papers are presented at poster sessions, 20% (171/855, long paper), 28% (119/419, short paper), 38% (30/80, demo paper), 23% (160/701, long paper), 24% (55/234, short paper), 54 extended short papers (6 pages), 26% (94/354, research track), 26% (37/143, applied ds track), 15% (23/151, journal track), 27.8% (164/592, overall), 9.8% (58/592, long presentation), 18.1% (107/592, regular), 28.2% (129/458, overall), 9.8% (45/458, long presentation), 18.3% (84/458, regular), 29.6% (91/307, overall), 12.7% (39/307, long presentation), 16.9% (52/307, regular), 40.4% (34/84, long presentation), 59.5% (50/84, short presentation)^, 16.3% (84/514 in which 3 papers are withdrawn/rejected after the acceptance), 28.4% (23/81, long presentation), 71.6% (58/81, short presentation)^, 30% (24/80, long presentation), 70% (56/80, short presentation)^, 29.8% (20/67, long presentation), 70.2% (47/67, short presentation)^, 53.8% (21/39, long presentation), 46.2% (18/39, short presentation)^. The VTU workshops accepts both short paper (4 pages) and long paper (8 pages). 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). The accelerated developments in the field of Artificial Intelligence (AI) hint at the need for considering Safety as a design principle rather than an option. Online. New theory and fundamentals of AI-aided design and manufacturing. The excellent papers will be recommended for publications in SCI or EI journals. At least one author of each accepted submission must be present at the workshop. We welcome full paper submissions (up to 8 pages, excluding references or supplementary materials). Washington DC, USA. There will be about 60~85 people to participate, including the program committee, invited speakers, panelists, authors of accepted papers, winners of the competition and other interested people. The first achievements in playing these games at super-human level were attained with methods that relied on and exploited domain expertise that was designed manually (e.g. After seventh highly successful events, the eighth Symposium on Visualization in Data Science (VDS) will be held at a new venue, ACM KDD 2022 as well as IEEE VIS 2022. 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. Naftali Cohen (JP Morgan Chase & New York University), Eren Kurshan (Bank of America & Columbia University), Senthil Kumar (Capital One), Susan Tibbs (Financial Institutions Regulatory Authority, FINRA), Tucker Balch (JP Morgan Chase & Georgia Institute of Technology), and Kevin Compher (Securities Exchange Commission). Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao. Submissions of technical papers can be up to 7 pages excluding references and appendices. Each accepted paper presentation will be allocated between 15 and 20 minutes. Why did so many AI/ML models fail during the pandemic? Integration of logical inference in training deep models. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. The main research questions and topics of interest include, but are not limited to: This will be a one day workshop, including four invited speakers, one panel session, a number of oral presentations of the accepted long papers and two poster sessions for all accepted papers including short and long. Novel AI-based techniques to improve modeling of engineering systems. 1, Sec. We hope this will help bring the communities of data mining and visualization more closely connected. ), 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). 1-39, November 2016. 2022. All submissions must be anonymous and conform to AAAI standards for double-blind review. DeepGAR: Deep Graph Learning for Analogical Reasoning. RL4ED is intended to facilitate tighter connections between researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). The AAAI Workshop on Machine Learning for Operations Research (ML4OR) builds on the momentum that has been directed over the past 5 years, in both the OR and ML communities, towards establishing modern ML methods as a first-class citizen at all levels of the OR toolkit. simulation, evaluation and experimentation. Adversarial attacking deep learning systems, Robust architectures against adversarial attacks, Hardware implementation and on-device deployment, Benchmark for evaluating model robustness, New methodologies and architectures for efficient and robust deep learning, December 3, 2021 Acceptance Notification, Applications of privacy-preserving AI systems, Differential privacy: theory and applications, Distributed privacy-preserving algorithms, Privacy preserving optimization and machine learning, Privacy preserving test cases and benchmarks. 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. A message will appear on your application form if there is a risk that the time required to process the application and to send the answer, in addition to the time you will need to acquire study permits, will be too long for you to arrive for the beginning of the session. Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. 1145/3394486.3403221. LOG 2022 LOG '22 . All accepted papers will be archived on the workshop website, but there will not be formal proceedings. The post-lunch session will feature a second keynote talk, two invited talks. Topics of interest include but are not limited to: Acronyms, i.e., short forms of long phrases, are common in scientific writing. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. Junxiang Wang and Liang Zhao. All extended abstracts and full papers are to be presented at the poster sessions. Small Molecule Generation via Disentangled Representation Learning. Topics of interest include, but are not limited to: Paper submissions will be in two formats: full paper (8 pages) and position paper (4 pages): The submission website ishttps://easychair.org/conferences/?conf=trase2022. The workshop will focus on two thrusts: 1) Exploring how we can leverage recent advances in RL methods to improve state-of-the-art technology for ED; 2) Identifying unique challenges in ED that can help nurture technical innovations and next breakthroughs in RL. In Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. Yuyang Gao and Liang Zhao. Novel ML methods in the computational material and physical sciences. Kyoto . While the research community is converging on robust solutions for individual AI models in specific scenarios, the problem of evaluating and assuring the robustness of an AI system across its entire life cycle is much more complex. Besides academia, many companies and institutions are researching on topics specific to their particular domains. Automatic fact/claim verification has recently become a topic of interest among diverse research communities. Association for the Advancement of Artificial Intelligence, The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada. chess, checkers). After seventh highly successful events, the eighth Symposium on Visualization in Data Science (VDS) will be held at a new venue, ACM KDD 2022 as well as IEEE VIS 2022. Consult the list of programs available in the next session. Accepted contributions will be made publicly available as non-archival reports, allowing future submissions to archival conferences or journals. Aug 14-18. We send a public call and we assume the workshop will be of interest to many AAAI main conference audiences; we expect 50 participants. Submissions including full papers (6-8 pages) and short papers (2-4 pages) should be anonymized and follow the AAAI-22 Formatting Instructions (two-column format) at https://www.aaai.org/Publications/Templates/AuthorKit22.zip. This workshop has no archival proceedings. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. 14, 2022: The information of Keynote Speakers is available at, Apr. 11, 2022: We have posted the list of accepted Workshops at, Apr. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. Papers can be submitted here as an extended abstract (4 pages limit excluding references) or a short paper (6 pages limit excluding references). Research efforts and datasets on text fact verification could be found, but there is not much attention towards multi-modal or cross-modal fact-verification. Submissions may consist of up to 4 pages plus one additional page solely for references. There is now a great deal of interest in finding better alternatives to this scheme. Oct 14, 2021: Abstract Deadline. 2999-3006, New Orleans, US, Feb 2018. [materials][data]. Workshop URL:https://rail.fzu.edu.cn/info/1014/1064.htm, Prof. Chi-Hua ChenEmail: [email protected] address: No.2, Xueyuan Rd., Fuzhou, Fujian, ChinaTelephone: +86-18359183858. At the same time, multimodal hate-speech detection is an important problem but has not received much attention. Liang Zhao, Feng Chen, and Yanfang Ye. 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. As far as we know, we are the first workshop to focus on practical deep learning in the wild for AI, which is of great significance. These challenges are widely studied in enterprise networks, but there are many gaps in research and practice as well as novel problems in other domains. The goal of this workshop is to bring together the optimal transport, artificial intelligence, and structured data modeling, gathering insights from each of these fields to facilitate collaboration and interactions. Papers must be between 4-8 pages with the AAAI submission format submitted to the track of regular paper, SUPERB or Zero Speech result paper. Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic. Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. convolutional neural network (CNN), recurrent neural network (RNN), etc.) the 33rd Annual Computer Security Applications Conference (ACSAC 2018), (acceptance rate: 20.1%), San Juan, Puerto Rico, USA, Dec 2018, accepted. Liang Zhao's Homepage - Emory University Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. At least one author of each accepted submission must register and present their paper at the workshop. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. 1799-1808. For each accepted paper, at least one author must attend the workshop and present the paper. Accepted papers will be published in the workshop proceedings. Geographical Mapping and Visual Analytics for Health Data, Biomedical Ontologies, Terminologies, and Standards, Bayesian Networks and Reasoning under Uncertainty, Temporal and Spatial Representation and Reasoning, Crowdsourcing and Collective Intelligence, Risk Assessment, Trust, Ethics, Privacy, and Security, Computational Behavioral/Cognitive Modeling, Health Intervention Design, Modeling and Evaluation, Applications in Epidemiology and Surveillance (e.g., Bioterrorism, Participatory Surveillance, Syndromic Surveillance, Population Screening), Hybrid methods, combining data driven and predictive forward models, biomedical signal analysis/modeling (EEG, ECG, PPG, EMG, fMRI, IMU, medical/clinical data, etc. Zheng Zhang and Liang Zhao. This one-day workshop will bring concentrated discussions on self-supervision for the field of speech/audio processing via keynote speech, invited talks, contributed talks and posters based on community-submitted high-quality papers, and the result representation of SUPERB and Zero Speech challenge. The Institute for Operations Research and the Management Sciences, [Submission deadline extended, June 3] KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, We are excited to announce our upcoming workshop at. 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. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. Liang Zhao, Jiangzhuo Chen, Feng Chen, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. Deep Generative Models for Spatial Networks. This is a 1-day workshop involving talks by pioneer researchers from respective areas, poster presentations, and short talks of accepted papers. The topics of interest include but are not limited to: Theoretical and Computational Optimal Transport: Optimal Transport-Driven Machine Learning: Optimal Transport-Based Structured Data Modeling: The full-day workshop will start with two long talks and one short talk in the morning. The desired LENGTH of the workshop: Full-day (~8 hours). Identification of key challenges and opportunities for future research. Instead of grading each piece of work individually, which can take up a bulk of extra time, intelligent scoring tools allow teachers the ability to have their students work automatically graded. We will receive the paper on the CMT system. Big data Journal (impact factor: 1.489), vo. Declarative languages and differentiable programming. Recent years have witnessed growing interest in human and AI systems with the increasing realisation that machines can indeed meet objectives specified but the real question becomes have they been given the right objectives. We especially welcome research from fields including but not limited to AI, human-computer interaction, human-robot interaction, cognitive science, human factors, and philosophy. Information extraction and information retrieval for scientific documents; Question answering and question generation for scholarly documents; Word sense disambiguation, acronym identification and expansion, and definition extraction; Document summarization, text mining, document topic classification, and machine reading comprehension for scientific documents; Graph analysis applications including knowledge graph construction and representation, graph reasoning and query knowledge graphs; Biomedical image processing, scientific image plagiarism detection, and data visualization; Code/Pseudo-code generation from text and im-age/diagram captioning, New language understanding resources such as new syn-tactic/semantic parsers, language models or techniques to encode scholarly text; Survey or analysis papers on scientific document under-standing and new tasks and challenges related to each scientific domain; Factuality, data verification, and anti-science detection. Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. Call for Participation The 3rd KDD Workshop on Data-driven Humanitarian Mapping and Policymaking solicits research papers, case studies, vision papers, software demos, and extended abstracts. [Bests of ICDM], Zheng Zhang and Liang Zhao. Please keep your paper format according to AAAI Formatting Instructions (two-column format). Junxiang Wang, Hongyi Li, Liang Zhao. Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong. KDD 2022. KDD 2022 KDD . SDU will be a one-day workshop. Liming Zhang, Dieter Pfoser, Liang Zhao. 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: [email protected]), Mark Fuge (University of Maryland), Olga Wodo (University of Buffalo), Payel Das (IBM), Soumalya Sarkar (Raytheon), Workshop website:https://adam-aaai2022.github.io/. We will also have a video component for remote participation. Securing personal information, genomics, and intellectual property, Adversarial attacks and defenses on biomedical datasets, Detecting and preventing spread of misinformation, Usable security and privacy for digital health information, Phishing and other attacks using health information, Novel use of biometrics to enhance security, Machine learning (including RL) security and resiliency, Automation of data labeling and ML techniques, Operational and commercial applications of AI, Explanations of security decisions and vulnerability of explanations. Researchers from related fields are invited to submit papers on the recent advances, resources, tools, and upcoming challenges for SDU. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. 10, pp. We encourage all the teams who participated in the challenge to join the workshop. Linguistic analysis of business documents. Deep Multi-attributed Graph Translation with Node-Edge Co-evolution. Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. The annual ACM SIGMOD/PODS Conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and . While most work on XAI has focused on opaque learned models, this workshop also highlights the need for interactive AI-enabled agents to explain their decisions and models. Supplemental Workshop site:https://rl4ed.org/aaai2022/index.html. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. 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. How can we develop solid technical visions and new paradigms about AI Safety? the 56th Design Automation Conference (DAC 2019), accepted, (acceptance rate: 20%), Las Vegas, US, 2019. 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.
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