kdd 2022 deadline kdd 2022 deadline

Check the CFP for details Deadline: ICDM 2020 . This is especially the case for non-traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities with the sheer size and ever-increasing growth and change rate of their data. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. 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. What techniques and approaches can be used to detect and effectively manage similar scenarios in the future? KDD 2022. We cordially welcome researchers, practitioners, and students from academia and industry who are interested in understanding and discussing how data scarcity and bias can be addressed in AI to participate. Frontiers in Big Data, accepted, 2021. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting.Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), (acceptance rate: 16.2%), Hawaii, USA, Feb 2019, accepted. These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. iDetective: An Intelligent System for Automatic Identification of Key Actors in Online Hack Forums. Expected attendance is 40-50 people. KDD 2022. Merge remote-tracking branch 'origin/master', 2. Submissions are due by 12 November 2021. Participants in the hack-a-thon will be asked to either register as a team or be randomly assigned to a team after registration. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. Deep Spatial Domain Generalization. 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. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. ", ACM Transactions on Spatial Algorithms and Systems (TSAS), (Acceptance Rate: 11%), Volume 2 Issue 4, Acticle No. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. 2020. We aim to bring together researchers in AI, healthcare, medicine, NLP, social science, etc. iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. upon methodologies and applications for extracting useful knowledge from data [1]. Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. 5, pp. Additional advantages are possible, including decreased computational resources to solve a problem, reduced time for the network to make predictions, reduced requirements for training set size, and avoiding catastrophic forgetting. This is a one-day workshop, planned with a 10-minute opening, 6 invited keynotes, ~6 contributed talks, 2 poster sessions, and 2 panel discussions. Handwritten recognition in business documents. For instance, advanced driver assistance systems and autonomous cars have been developed based on AI techniques to perform forward collision warning, blind spot monitoring, lane departure warning systems, traffic sign recognition, traffic safety, infrastructure management and congestion, and so on. Keynotes and invited talks: Several keynotes and invited talks by leading researchers in the area will be presented. All papers will be peer-reviewed, single-blinded (i.e., please include author names/affiliations/email addresses on your first page). anomaly detection, and ensemble learning. All submissions must be anonymous and conform to AAAI standard for double-blind review. Examples of the datasets which may be considered are the DBTex Radiology Mammogram dataset and the Johns Hopkins COVID-19 case reports. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Washington DC, USA. 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. Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, Bill Wuest, Amarda Shehu, Liang Zhao. Our preliminary plan for the schedule is as following , DEFACTIFY@AAAI-22 Program [tentative]9:00AM-9:15AMInaugurationA brief summary of the shared tasks number of participants, best results, Session 1 multimodal fact checkingWorkshop papers 9:30AM 10:30AM, 11:00AM 12:00pmInvited talk 1 Prof. Rada Mihalcea, University of Michigan, Session 2 Best 4/5 papers from FACTIFY & MEMOTION shared taskWorkshop papers 1:00PM 2:00PM, 2:00PM 3:30PMInvited talk 2 Prof. LOUIS-PHILIPPE MORENCY, CMU, Session 2 multimodal hate speechWorkshop papers 4:00PM 5:00PM. 4701-4707, San Francisco, California, USA, Feb 2017. Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. Any participant who experiences unacceptable behavior may contact any current member of the SIGMOD Executive Committee, the PODS Executive Committee, DBCares, or this year's D&I co-chairs Pnar Tzn (pito@itu.dk) and Renata Borovica-Gajic (renata.borovica@unimelb.edu.au). In fact, the increasingly digitized education tools and the popularity of online learning have produced an unprecedented amount of data that provides us with invaluable opportunities for applying AI in education. Short or position papers of up to 4 pages are also welcome. The paper submissions must be in pdf format and use the AAAI official templates. This cookie is set by GDPR Cookie Consent plugin. Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning. We solicit papers describing significant and innovative research and applications to the field of job marketplaces. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. Representation learning, distributed representations learning and encoding in natural language processing for financial documents; Synthetic or genuine financial datasets and benchmarking baseline models; Transfer learning application on financial data, knowledge distillation as a method for compression of pre-trained models or adaptation to financial datasets; Search and question answering systems designed for financial corpora; Named-entity disambiguation, recognition, relationship discovery, ontology learning and extraction in financial documents; Knowledge alignment and integration from heterogeneous data; Using multi-modal data in knowledge discovery for financial applications; Data acquisition, augmentation, feature engineering, and analysis for investment and risk management; Automatic data extraction from financial fillings and quality verification; Event discovery from alternative data and impact on organization equity price; AI systems for relationship extraction and risk assessment from legal documents; Accounting for Black-Swan events in knowledge discovery methods. Can AI achieve the same goal without much low-level supervision? Multi-objective Deep Data Generation with Correlated Property Control. For each accepted paper, at least one author must attend the workshop and present the paper. Position papers are welcome. The submission website ishttps://easychair.org/conferences/?conf=fl-aaai-22. Adaptive Kernel Graph Neural Network. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. 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. [Call for papers] KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, CFP: IJCAI 2021 Reinforcement Learning for Intelligent Transportation Systems Workshop, Second Workshop on Marketplace Innovation. The theme of the hack-a-thon will be decided before submission is closed and will be focused around finding creative solutions to novel problems in health. 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. We accept two types of submissions full research paper no longer than 8 pages (including references) and short/poster paper with 2-4 pages. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. Adverse event detection by integrating Twitter data and VAERS. a concise checklist by Prof. Eamonn Keogh (UC Riverside). IBM Research, 2018. KDD 2022. RAISAs systems-level perspective will be emphasized via three main thrusts: AI threat modeling, AI system robustness, explainable AI, system lifecycle attacks, system verification and validation, robustness benchmarks and standards, robustness to black-box and white-box adversarial attacks, defenses against training, operational and inversion attacks, AI system confidentiality, integrity, and availability, AI system fairness and bias. The 19th International Conference on Data Mining (ICDM 2019), long paper, (acceptance rate: 9.08%), Beijing, China. chess, checkers). Interpretable Molecular Graph Generation via Monotonic Constraints. 2020. Jos Miguel Hernndez-Lobato, University of CambridgeProf. 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. 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. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. 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 . We received 38 paper submissions and accepted 23 of them. The following paper categories are welcome: Submission site:https://sites.google.com/view/eaai-ws-2022/call, Silvia Tulli (Dept. Authors are strongly encouraged to make data and code publicly available whenever possible. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. The workshop on Robust Artificial Intelligence System Assurance (RAISA) will focus on research, development and application of robust artificial intelligence (AI) and machine learning (ML) systems. We invite submission of papers describing innovative research on all aspects of knowledge discovery and data science, ranging from theoretical foundations to novel models and algorithms for data science problems in science, business, medicine, and engineering. All papers must be submitted in PDF format, using the AAAI-22 author kit. Submission Guidelines in Proceedings of the SIAM International Conference on Data Mining (SDM 2015), (acceptance rate: 22%), Vancouver, BC, pp. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. Each accepted paper presentation will be allocated between 15 and 20 minutes. "Efficient Global String Kernel with Random Features: Beyond Counting Substructures", In the Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019), research track (acceptance rate: 14.2%), accepted, Alaska, USA, Aug 2019. Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self, Rupinder Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Chris Kuhlman, Achla Marathe, Liang Zhao, Ting Hua, Feng Chen, et al.. "'Beating the news' with EMBERS:forecasting civil unrest using open source indicators." Transformations in many fields are enabled by rapid advances in our ability to acquire and generate data. Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with human agents. 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. Pattern Recognition, (impact factor: 7.196),112 (2021): 107711. LOG 2022 LOG '22 . Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. 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/. 4 pages), and position (max. have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). Second, psychological experiments in laboratories and in the field, in partnership with technology companies (e.g., using apps), to measure behavioral outcomes are being increasingly used for informing intervention design. Our intent is to facilitate new AI/ML advances for core engineering design, simulation, and manufacturing. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. Integration of neuro and symbolic approaches. ASPLOS 2023 will be moving to three submission deadlines. We will end the workshop with a panel discussion by invited speakers from different fields to enlist future directions. Attendance is open to all. Novel AI-based techniques to improve modeling of engineering systems. While original contributions are preferred, we also invite submissions of high-quality work that has recently been published in other venues or is concurrently submitted. "Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning." Notable examples include the information bottleneck (IB) approach on the explanation of the generalization behavior of DNNs and the information maximization principle in visual representation learning. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. One recommended setting for Latex file is:\documentclass[sigconf, review]{acmart}. Chen Ling, Hengning Cao, Liang Zhao. Liming Zhang, Dieter Pfoser, Liang Zhao. KDD 2022 is a dual-track conference that provides distinct programming in research and applied data science. Three specific roles are part of this format: session chairs, presenters and paper discussants. Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. IEEE, 2014. Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2021), (acceptance rate: 21.0%), accepted. Autonomous vehicles can share their detected information (e.g., traffic signs, collision events, etc.) a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette). 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. Attendance is open to all, subject to any room occupancy constraints. text, images, and videos). 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. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. "Misinformation Propagation in the Age of Twitter." At the same time, multimodal hate-speech detection is an important problem but has not received much attention. 2022. and facilitate discussions and collaborations in developing trustworthy AI methods that are reliable and more acceptable to physicians. 2022. Accepted papers are likely to be archived. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. [Bests of ICDM]. Submitted papers will be assessed based on their novelty, technical quality, potential impact, and clarity of writing. Connor Coley, Massachusetts Institute of TechnologyProf. Template guidelines are here:https://www.acm.org/publications/proceedings-template. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. SDU will be a one-day workshop. Deadline: FSE 2023. ), 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). Short or position papers of up to 4 pages are also welcome. Babies learn their first language through listening, talking, and interacting with adults. Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. The AAAI author kit can be downloaded from:https://www.aaai.org/Publications/Templates/AuthorKit22.zip. 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 third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22) builds on the success of previous years PPAI-20 and PPAI-21 to provide a platform for researchers, AI practitioners, and policymakers to discuss technical and societal issues and present solutions related to privacy in AI applications. IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 24.31), accepted. Papers must be in PDF format, in English, and formatted according to the AAAI template. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Prediction-time Efficient Classification Using Feature Computational Dependencies. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. Malicious attacks for ML models to identify their vulnerability in black-box/real-world scenarios. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. A primary reason for this is the inherent long-tailed nature of our world, and the need for algorithms to be trained with large amounts of data that includes as many rare events as possible. [Best Paper Award Shortlist]. Modeling Health Stage Development of Patients with Dynamic Attributed Graphs in Online Health Communities. Generative Adversarial Learning of Protein Tertiary Structures. 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. All extended abstracts and full papers are to be presented at the poster sessions. December, 12-16, 2022. All submissions must be in PDF format and formatted according to the new Standard AAAI Conference Proceedings Template. Disentangled Spatiotemporal Graph Generative Model. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning. 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). How to do good research, Get it published in SIGKDD and get it cited! The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. NOTE: Mandatory abstract deadline: 2022-08-08 Deadline: AAAI 157. 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. 3434-3440, Melbourne, Australia, Aug 2017. Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada AAAI is pleased to present the AAAI-22 Workshop Program.