kdd 2022 deadline kdd 2022 deadline

2022. Submissions will be peer-reviewed, single-blinded, and assessed based on their novelty, technical quality, significance, clarity, and relevance regarding the workshop topics. 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. We will also select some of the best posters for spotlight talks (2 minutes each). arXiv preprint arXiv:2207.09542 (2022). ISBN: 978-981-16-6053-5. Both the research papers track and the applied data science papers track will take . Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), pp. An increasing world population, coupled with finite arable land, changing diets, and the growing expense of agricultural inputs, is poised to stretch our agricultural systems to their limits. Integration of logical inference in training deep models. You also have the option to opt-out of these cookies. 10, pp. KDD 2022 : 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Conference Series : Knowledge Discovery and Data Mining Link: https://kdd.org/kdd2022/ Call For Papers [Empty] Related Resources KDD 2023 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING Programming Languages, Domain specific languages, Libraries and software tools for integration of various learning and reasoning paradigms. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). and deep learning techniques (e.g. Knowledge representation for business documents. We encourage long papers, short papers and demo papers. Optimal transport-based analysis of structured data, such as networks, meshes, sequences, and so on; The applications of optimal transport in molecule analysis, network analysis, natural language processing, computer vision, and bioinformatics. Winter. For questions on submission and the workshop, please send email through the following link: Track 1: Tony Qin (Lyft), Rui Song (NC State & Amazon), Hongtu Zhu (UNC), Michael Jordan (Berkeley), Track 2: Liangjie Hong (LinkedIn), Mohammed Korayem (CareerBuilder), Haiyan Luo (Indeed). Transfer learning methods for business document reading and understanding. What approaches emerge in building fundamentally robust and adaptive AI/ML systems? The workshop follows a single-blind reviewing process. Yuanqi du, George Mason University, USA; Jian Pei, Simon Fraser University, Canada; Charu Aggarwal, IBM Research AI, USA; Philip S. Yu, University of Illinois at Chicago, USA; Xuemin Lin, University of New South Wales, Australia; Jiebo Luo, University of Rochester, USA; Lingfei Wu, JD.Com Silicon Valley Research Center, USA; Yinglong Xia, Facebook AI, USA; Jiliang Tang, Michigan State University, USA; Peng Cui, Tsinghua University, China; William L. Hamilton, McGill University, Canada; Thomas Kipf, University of Amsterdam, Netherlands, Workshop URL:https://deep-learning-graphs.bitbucket.io/dlg-aaai22/. This cookie is set by GDPR Cookie Consent plugin. 10 (2014): e110206. 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. Declarative languages and differentiable programming. Workshop URL:https://rail.fzu.edu.cn/info/1014/1064.htm, Prof. Chi-Hua ChenEmail: chihua0826@gmail.comPostal address: No.2, Xueyuan Rd., Fuzhou, Fujian, ChinaTelephone: +86-18359183858. 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. Qingzhe Li, Liang Zhao, Jessica Lin and Yi-ching Lee. Submissions will undergo double blind review. Data science is the practice of deriving insights from data, enabled by statistical modeling, computational methods, interactive visual analysis, and domain-driven problem solving. This workshop wants to emphasize on the importance of integrative paradigms for solving the new wave of AI applications. Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic. VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. Videos have become an omnipresent source of knowledge: courses, presentations, conferences, documentaries, live streams, meeting recordings, vlogs. All papers will be peer reviewed, single-blinded. 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. We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. information bottleneck principle). 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. This workshop on Trustworthy Autonomous Systems Engineering (TRASE) offers an opportunity to highlight state of the art research in trustworthy autonomous systems, as well as provide a vision for future foundational and applied advances in this critical area at the intersection of AI and Cyber-Physical Systems. [Best Paper Candidate]. Data mining systems and platforms, and their efficiency, scalability, security and privacy. We encourage all the teams who participated in the challenge to join the workshop. 2020. Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. The AAAI-22 workshop program includes 39 workshops covering a [] The goal of this workshop is to connect researchers in self-supervision inside and outside the speech and audio fields to discuss cutting-edge technology, inspire ideas and collaborations, and drive the research frontier. How can we make AI-based systems more ethically aligned? 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. To push forward the research on acronym understanding in scientific text, we propose two shared tasks on acronym extraction (i.e., recognizing acronyms and phrases in text) and disambiguation (i.e., finding the correct expansion for an ambiguous acronym). Yevgeniy Vorobeychik (Washington University in St. Louis), Bruno Sinopoli (Washington University in St. Louis), Jinghan Yang (Washington University in St. Louis), Bo Li (UIUC), Atul Prakash (University of Michigan), Supplemental Workshop site:https://jinghany.github.io/trase2022/. 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. 1466-1469. In addition, several invited speakers with distinguished professional background will give talks related the frontier topics of GNN. How can we develop solid technical visions and new paradigms about AI Safety? Xiaojie Guo, Yuanqi Du, Liang Zhao. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. AI is one of these transformative technologies that is now achieving great successes in various real-world applications and making our life more convenient and safer. We invite participants to submit papers by the 12th of November, based on but not limited to, the following topics: RL in various formalisms: one-shot games, turn-based, and Markov games, partially-observable games, continuous games, cooperative games; deep RL in games; combining search and RL in games; inverse RL in games; foundations, theory, and game-theoretic algorithms for RL; opponent modeling; analyses of learning dynamics in games; evolutionary methods for RL in games; RL in games without the rules; search and planning; and online learning in games. For example, FL is still at the risk of various kinds of attacks that may result in leakage of individual data source privacy or degraded joint model accuracy. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Workshops are one day unless otherwise noted in the individual descriptions. Short or position papers of up to 4 pages are also welcome. 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. Our intent is to facilitate new AI/ML advances for core engineering design, simulation, and manufacturing. RES: A Robust Framework for Guiding Visual Explanation. ITCI22 will be a one-day workshop. Ferdinando Fioretto (Syracuse University), Emma Frejinger (Universit de Montral), Elias B. Khalil (University of Toronto), Pashootan Vaezipoor (University of Toronto). 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. The submitted papers written in English must be in PDF format according to the AAAI camera ready style. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. The aim of the hack-a-thon is not only to foster innovation and potentially provide answers to outstanding research problems, but rather to engage the community and create new collaborations. Microsoft's Conference Management Toolkit is a hosted academic conference management system. Following this AAAI conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". Welcome to PAKDD2022. The VTU workshops accepts both short paper (4 pages) and long paper (8 pages). 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. The workshop organizers invite paper submissions on the following (and related) topics: This workshop will be a one-day workshop, featuring invited speakers, poster presentations, and short oral presentations of selected accepted papers.