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Our goal is to build a stronger community of researchers exploring these methods, and to find synergies among these related approaches and alternatives. Zero Speech challenge is to build language models only based on audio or audio-visual information, without using any textual input. Papers will be submitted to OpenReview system: Waiting for approval,https://openreview.net/forum?id=6uMNTvU-akO, Workshop Chair:Parisa Kordjamshidi, +1-2174187004, kordjams@msu.edu, Organizing Committee:Parisa Kordjamshidi (Michigan State University, kordjams@msu.edu), Behrouz Babaki (Mila/HEC Montreal, behrouz.babaki@mila.quebec), Sebastijan Dumani (KU Leuven, sebastijan.dumancic@cs.kuleuven.be), Alex Ratner (University of Washington, ajratner@cs.washington.edu), Hossein Rajaby Faghihi (Michigan State University, rajabyfa@msu.edu), Hamid Karimian (Michigan State University, karimian@msu.edu), Organizing Committee:Dan Roth (University of Pennsylvania, danroth@seas.upenn.edu) and Guy Van Den Broeck (University of California Los Angeles, guyvdb@cs.ucla.edu), Supplemental workshop site:https://clear-workshop.github.io. There is now a great deal of interest in finding better alternatives to this scheme. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. Creative Commons Attribution-Share Alike 3.0 License, 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, Knowledge Discovery and Data Mining Conference, 22nd ACM SIGKDD international conference on knowledge discovery and data mining, 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 18th ACM SIGKDD Knowledge Discovery and Data Mining, The 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. The fundamental mechanism of an online marketplace is to match supply and demand to generate transactions, with objectives considering service quality, participants experience, financial and operational efficiency. Big data Journal (impact factor: 1.489), vo. Nonetheless, human-centric problems (such as activity recognition, pose estimation, affective computing, BCI, health analytics, and others) rely on information modalities with specific spatiotemporal properties. The challenge requires participants to build competitive models for diverse downstream tasks with limited labeled data and trainable parameters, by reusing self-supervised pre-trained networks. The goal of this workshop is to bring together the causal inference, artificial intelligence, and behavior science communities, gathering insights from each of these fields to facilitate collaboration and adaptation of theoretical and domain-specific knowledge amongst them. Thank you for all your contributions, our, Paper submission deadline is now extended to. Submissions should follow the AAAI 2022 formatting guidelines and the AAAI 2022 standards for double-blind review including anonymous submission. In general, AI techniques are still not widely adopted in the real world. ACM, New York, NY, USA, 10 pages. The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. in Proceedings of the SIAM International Conference on Data Mining (SDM 2015), (acceptance rate: 22%), Vancouver, BC, pp. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." The cookie is used to store the user consent for the cookies in the category "Other. VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. We are in a conversation with some publishers once they confirm, we will announce accordingly. However, most models and AI systems are built with conservative operating environment assumptions due to regulatory compliance concerns. Check the deadlines for submitting your application. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. 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. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. 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. The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. 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. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Note: The workshop is a collaboration between NASSMA organisation, Deepmind and UM6P. 4 pages), and position (max. Undergraduate (bachelor's, certificate, etc. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. At the same time, multimodal hate-speech detection is an important problem but has not received much attention. The 21st Web Conference (WWW 2022), (Acceptance Rate: 17.7%), accepted. Submission Guidelines Onn Shehory, Bar Ilan University (onn.shehory@biu.ac.il), Eitan Farchi, IBM Research Haifa (farchi@il.ibm.com), Guy Barash, Western Digital (Guy.Barash@wdc.com), Supplemental workshop site:https://sites.google.com/view/edsmls-2022/home. Liang Zhao, Junxiang Wang, and Xiaojie Guo. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. . We invite paper submission with a focus that aligns with the goals of this workshop. Multilingual document understanding methods and frameworks. Adaptive Kernel Graph Neural Network. We hope to build upon that success. "Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning." Summer. Han Wang, Hossein Sayadi, Avesta Sasan, Houman Homayoun, Liang Zhao, Tinoosh Mohsenin, Setareh Rafatirad. Attendance is open to all; at least one author of each accepted paper must be virtually present at the workshop. Small Molecule Generation via Disentangled Representation Learning. 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. The workshop will be a one-day meeting and will include a number of technical sessions, a virtual poster session where presenters can discuss their work, with the aim of further fostering collaborations, multiple invited speakers covering crucial challenges for the field of privacy-preserving AI applications, including policy and societal impacts, a tutorial talk, and will conclude with a panel discussion. Options include pruning a trained network or training many networks automatically. Xiaosheng Li, Jessica Lin, Liang Zhao. VDS will bring together domain scientists and methods researchers (including data mining, visualization, usability and HCI, data management, statistics, machine learning, and software engineering) to discuss common interests, talk about practical issues, and identify open research problems in visualization in data science. All papers must be submitted in PDF format, using the AAAI-22 author kit. Big Data 2022 December 13-16, 2022. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. 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 cookie is set by GDPR Cookie Consent plugin. NOTE: Mandatory abstract deadline on Oct 13, 2022. 2022. Applications of causal inference and discovery in machine learning/deep learning motivated by information-theoretic approaches (e.g. Short or position papers of up to 4 pages are also welcome. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. Attendance is open to all. Invited speakers, panels, poster sessions, and presentations. Andrew White, University of RochesterDr. We expect 50~75 participants and potentially more according to our past experiences. Amir A. Fanid, Monireh Dabaghchian, Ning Wang, Pu Wang, Liang Zhao, Kai Zeng. Frontiers in Big Data, accepted, 2021. search, ranking, recommendation, and personalization. We are interested in a broad range of topics, both foundational and applied. 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. Submissions that do not meet the formatting requirements will be rejected without review. We invite submission of papers describing innovative research and applications around the following topics. 19-25, 2016. 5, pp. A final tribute was paid on Saturday to former Coalition Avenir Qubec (CAQ) minister Nadine Girault, who died of lung cancer last month at age 63 . Submissions will be peer-reviewed, single-blinded, and assessed based on their novelty, technical quality, significance, clarity, and relevance regarding the workshop topics. All papers must be submitted in PDF format using the AAAI-22 author kit. a concise checklist by Prof. Eamonn Keogh (UC Riverside). In addition, broad deployment of ML software in networked systems inevitably exposes ML software to attacks. The biomedical space has seen a flurry of activity recently, and cyber criminals have amplified their efforts with health-related phishing attacks, spreading misinformation, and intruding into health infrastructure. The excellent papers will be recommended for publications in SCI or EI journals. GraphGT: Machine Learning Datasets for Deep Graph Generation and Transformation. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). 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. Additional information about formatting and style files is available here: : Full papers are limited to a total of 6 pages, including all content and references. Algorithms for secure and privacy-aware machine learning for AI. "Knowledge-enhanced Neural Machine Reasoning: A Review." 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). Papers will be peer-reviewed and selected for spotlight and/or poster presentation. This manual extraction process is usually inefficient, error-prone, and inconsistent. Frontiers in Neurorobotics, (impact factor: 2.574), accepted. Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad,. Topics include but not limited to: Large-scale and novel targeting technologies, Fraud, fairness, explainability and privacy, Intelligent assistants in job hunting and hiring automation, Large-scale and high performing data infrastructure, data analysis and tooling, Economics and causal inference in online jobs marketplace, Large-scale analytics of user behaviors in online jobs marketplace. Its capabilities have expanded from processing structured data (e.g. 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. Out of these, around 20~30 papers are accepted. 2022. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. 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. Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. 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/. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. Neil T. Heffernan, Worcester Polytechnic Institute (Worcester, MA, USA), Andrew S. Lan, University of Massachusetts Amherst (Amherst, MA, USA), Anna N. Rafferty, Carleton College (Northfield, MN, USA), Adish Singla, Max Planck Institute for Software Systems (Saarbrucken, Germany). Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. The 9th International Conference on Learning Representations (ICLR 2021), (acceptance rate: 28.7%), accepted. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. 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. 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. arXiv preprint arXiv:2212.03954 (2022). International Journal of Digital Earth, (impact factor: 3.097), 25 Aug 2020, https://doi.org/10.1080/17538947.2020.1809723. Although machine learning (ML) approaches have demonstrated impressive performance on various applications and made significant progress for AI, the potential vulnerabilities of ML models to malicious attacks (e.g., adversarial/poisoning attacks) have raised severe concerns in safety-critical applications. ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices. Long papers (up to 6 pages + references) and extended abstracts (2 pages + references) are welcome, including resubmissions of already accepted papers, work-in-progress, and position papers. Send this CFP to us by mail: cfp@ourglocal.org. Yuyang Gao, Lingfei Wu, Houman Homayoun, and Liang Zhao. Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting. Pourya Hoseinip, Liang Zhao, and Amarda Shehu. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. In light of these issues, and the ever-increasing pervasiveness of AI in the real world, we seek to provide a focused venue for academic and industry researchers and practitioners to discuss research challenges and solutions associated with building AI systems under data scarcity and/or bias. https://doi.org/10.1007/s10707-019-00376-9. We encourage authors to contact the organizers to discuss possible overlap. Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic. Keynotes and invited talks: Several keynotes and invited talks by leading researchers in the area will be presented. The objective of this workshop is to discuss the winning submissions of the Submissions to the Amazon KDD Cup 2022 issingle-blind (author names and affiliations should be listed). We hope this will help bring the communities of data mining and visualization more closely connected. Deep Graph Learning for Circuit Deobfuscation. Time Series Clustering in Linear Time Complexity. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. 105, no. This year the AICS emphasis will be on practical considerations in the real world when deploying AI systems for security with a special focus on convergence of AI and cyber-security in the biomedical field. We invite submissions from participants who can contribute to the theory and applications of modeling complex graph structures such as hypergraphs, multilayer networks, multi-relational graphs, heterogeneous information networks, multi-modal graphs, signed networks, bipartite networks, temporal/dynamic graphs, etc. Researchers from related fields are invited to submit papers on the recent advances, resources, tools, and upcoming challenges for SDU. Topics include, but our not limited to: learning optimization models from data, constraint and objective learning, AutoAI, especially if combined with decision optimization models or environments, AutoRL, incorporating the inaccuracy of the automatically learnt models in the decision making process, and using machine learning to efficiently solve combinatorial optimization models. Prediction-time Efficient Classification Using Feature Computational Dependencies. System reports should also follow the AAAI 2022 formatting guidelines and have 4-6 pages including references. ACM Computing Surveys (CSUR), (impact factor: 10.28), accepted. We are excited to continue promoting innovation in self-supervision for the speech/audio processing fields and inspiring the fields to contribute to the general machine learning community. Deep learning has achieved significant success for artificial intelligence (AI) in multiple fields. We invite submissions on a wide range of topics, spanning both theoretical and practical research and applications. Well also host a competition on adversarial ML along with this workshop. of London). Lastly, learning joint modalities is of interest to both Natural Language Processing (NLP) and Computer Vision (CV) forums. 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. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. The workshop invites contribution to novel methods, innovations, applications, and broader implications of SSL for processing human-related data, including (but not limited to): In addition to the above, papers that consider the following are also invited: Manuscripts that fit only certain aspects of the workshop are also invited. upon methodologies and applications for extracting useful knowledge from data [1]. 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. Junxiang Wang, Junji Jiang, Liang Zhao. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, and Chang-Tien Lu. 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. I recommend highly motivated students to reach out to me way earlier than the admission deadline, and figure out a research project project with me, with the goal of a publication. Association for the Advancement of Artificial Intelligence, The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada. At least one author of each accepted submission must be present at the workshop. ), The workshop will be organized as half-day event with 2 invited speakers, follow by presentation from accepted papers (both ordinary papers, and shared task paper). 2022. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. In addition, any other work on dialog research is welcome to the general technical track. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. In nearly all applications, reliability, safety, and security of such systems is a critical consideration. 14, 2022: The information of Keynote Speakers is available at, Apr. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2020), (acceptance rate: 20.6%), accepted. CoRL 2023 97 days 17h 29m 15s November 06-09, 2023. [code] 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. Data Mining Conference Acceptance Rate. The scope of the workshop includes, but is not limited to, the following areas: We also invite participants to an interactive hack-a-thon. Oct 14, 2021: Abstract Deadline. 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 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. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. Paper Submission Deadline: May 26, 2022 Author Notification: June 20, 2022 Camera Ready: July 9, 2022 Workshop: August . While classical security vulnerabilities are relevant, ML techniques have additional weaknesses, some already known (e.g., sensitivity to training data manipulation), and some yet to be discovered. Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. arXiv preprint arXiv:2207.09542 (2022). Submission instructions will be available at the workshop web page. DOI:https://doi.org/10.1145/3339823. System reports will be presented during poster sessions. Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. How do metrics of capability and generality, and the trade-offs with performance affect safety? Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. The post-launch session includes the invited talks, shared task winners presentations, and a panel discussion on the resources, findings, and upcoming challenges. Research track papers reporting the results of ongoing or new research, which have not been published before. It is a forum to bring attention towards collecting, measuring, managing, mining, and understanding multimodal disinformation, misinformation, and malinformation data from social media. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). 639-648, Nov 2015. No supplement is allowed for extended abstracts. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . This policy also applies to papers that overlap substantially in technical content with papers previously published, accepted, or under review. Are you sure you want to create this branch? We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. . Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. Papers that are under review at another conference or journal are acceptable for submission at this workshop, but we will not accept papers that have already been accepted or published at a venue with formal proceedings (including KDD 2022). Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. 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. 2020. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. Qingzhe Li, Liang Zhao, Jessica Lin and Yi-ching Lee. This workshop covers (but not limited to) the following topics: , It is a one day workshop and includes: invited talks, interactive discussions, paper presentations, shared task presentations, poster session etc.
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