Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. Data Mining Conference Acceptance Rate. 2022. These lead to security considerations: (1) securing personal health information, genetic material, intellectual property, and digital health records, (2) balancing privacy rights and data ownership concerns in solutions using network and mobile data, (3) defending AI for biology use cases to deter automated attacks at scale. have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. Semantic understanding of business documents. Attendance is open to all. Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning. In general, AI techniques are still not widely adopted in the real world. Zero Speech challenge is to build language models only based on audio or audio-visual information, without using any textual input. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. Deadlines are shown in America/Los_Angeles time. Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. [slides] "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. However, theoreticians and practitioners of AI and Safety are confronted with different levels of safety, different ethical standards and values, and different degrees of liability, that force them to examine a multitude of trade-offs and alternative solutions. The growing popularity of NAS methods demonstrates the communitys hunger for better ways of choosing or evolving network architectures that are well-matched to the problem at hand. Xiaosheng Li, Jessica Lin, Liang Zhao. Please email to Lingfei Wu: lwu@email.wm.edu for any query. After the submission deadline, the names and order of authors cannot be changed. Computer Communications, (impact factor: 3.34), Elsevier, vo. Please refer tohttps://rl4ed.org/aaai2022/index.htmlfor additional information. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), short paper (acceptance rate: 19.9%), Singapore, Dec 2018, accepted. Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. 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. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. GNES: Learning to Explain Graph Neural Networks. Toward Model Parallelism for Deep Neural Network based on Gradient-free ADMM Framework. Amitava Das (Wipro AI Labs; amitava.santu@gmail.com), Workshop Chairs: Amitava Das (Wipro AI Labs) [India], Amit Sheth (University of South Carolina) [USA], Tanmoy Chakraborty (IIIT Delhi) [India], Asif Ekbal (IIT Patna) [India], Chaitanya Ahuja (CMU) [USA], Parth Patwa (UCLA) [USA], Parul Chopra (CMU) [USA], Amrit Bhaskar (ASU) [USA], Nethra Gunti (IIIT Sri City) [USA], Sathyanarayanan R. (IIIT Sri City) [India], Shreyash Mishra (IIIT Sri City) [India], S. Suryavardan (IIIT Sri City) [India], Vishal Pallagani (University of South Carolina), Supplemental workshop site:https://aiisc.ai/defactify/. Realizing the vision of Document Intelligence remains a research challenge that requires a multi-disciplinary perspective spanning not only natural language processing and understanding, but also computer vision, layout understanding, knowledge representation and reasoning, data mining, knowledge discovery, information retrieval, and more all of which have been profoundly impacted and advanced by deep learning in the last few years. The official dates for submitting an application are detailed below, but see the exact deadline posted on the Description Page for the program of study. Xiaosheng Li, Jessica Lin, and Liang Zhao. Application fees are not refundable. arXiv preprint arXiv:2212.03954 (2022). 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. This has created a strong demand for transcript understanding. However, FL also faces multiple challenges that may potentially limit its applications in real-world use scenarios. 5 (2014): 1447-1459. 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. The papers may consist of up to seven pages of technical content plus up to two additional pages for references. 32, no. 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. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016), regular paper, (acceptance rate: 8.5%), pp. 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. However, despite increasing interest from various subfields, AI/ML techniques are yet to fulfill their full promise in achieving these advances. May 8, 2022: Student Travel Awards announcement is, Apr. Government day with NSF, NIH, DARPA, NIST, and IARPA, Local industries in the DC Metro Area, including the Amazons second headquarter, New initiatives at KDD 2022: undergraduate research and poster session, Early career research day with postdoctoral scholars and assistant professors in a mentoring workshop and panel, Workshops and hands-on tutorials on emerging topics. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. 25, 2022: We have announced Call for Nominations: , Mar. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. Submission site:https://cmt3.research.microsoft.com/AAAI2022HCSSL/Submission/Index, Ali Etemad (Queens University, ali.etemad@queensu.ca), Ali Etemad (Queens University, ali.etemad@queensu.ca), Ahmad Beirami (Facebook AI, ahmad.beirami@gmail.com), Akane Sano (Rice University, akane.sano@rice.edu), Aaqib Saeed (Philips Research & University of Cambridge, aqibsaeed@protonmail.com), Alireza Sepas-Moghaddam (Socure, alireza.sepasm@socure.com), Mathilde Caron (Inria & Facebook AI, mathilde@fb.com), Pritam Sarkar (Queens University & Vector Institute, pritam.sarkar@queensu.ca), Huiyuan Yang (Rice University, hy48@rice.edu), Supplemental website:https://hcssl.github.io/AAAI-22/. Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng and Liang Zhao. Authors of accepted papers will be invited to participate. 5, pp. iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. 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. We welcome the submissions in the following two formats: The submissions should adhere to theAAAI paper guidelines. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. Functional Connectivity Prediction with Deep Learning for Graph Transformation. robust and interpretable natural language processing for healthcare. Aryan Deshwal (Washington State University, aryan.deshwal@wsu.edu), Syrine Belakaria (Washington State University, syrine.belakaria@wsu.edu), Cory Simon (Oregon State University, cory.simon@oregonstate.edu), Jana Doppa (Washington State University, jana.doppa@wsu.edu), Yolanda Gil (University of Southern California, gil@isi.edu), Supplemental workshop site:https://ai-2-ase.github.io/. Federated learning (FL) is one promising machine learning approach that trains a collective machine learning model using sharing data owned by various parties. The workshop page ishttps://sites.google.com/view/aaaiwfs2022, and it will include the most up-to-date information, including the exact schedule. 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. The AAAI author kit can be downloaded from:https://www.aaai.org/Publications/Templates/AuthorKit22.zip. It highlights the importance of declarative languages that enable such integration for covering multiple formalisms at a high-level and points to the need for building a new generation of ML tools to help domain experts in designing complex models where they can declare their knowledge about the domain and use data-driven learning models based on various underlying formalisms. Benchmarks to reliably evaluate attacks/defenses and measure the real progress of the field. For further information, please have a look at the call for contributions. Martin Michalowski, PhD, FAMIA (Co-chair), University of Minnesota; Arash Shaban-Nejad, PhD, MPH (Co-chair), The University of Tennessee Health Science Center Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics; Simone Bianco, PhD (Co-chair), IBM Almaden Research Center; Szymon Wilk, PhD, Poznan University of Technology; David L. Buckeridge, MD, PhD, McGill University; John S. Brownstein, PhD, Boston Childrens Hospital, Workshop URL:http://w3phiai2022.w3phi.com/. Novel AI-based techniques to improve modeling of engineering systems. 507-516, Singapore, Nov 2017. Disentangled Spatiotemporal Graph Generative Model. "Bridging the gap between spatial and spectral domains: A survey on graph neural networks." Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad. What techniques and approaches can be used to detect and effectively manage similar scenarios in the future? Ranking, acceptance rate, deadline, and publication tips. Factorized Deep Generative Models for End-to-End Trajectory Generation with Spatiotemporal Validity Constraints. "TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction", the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2019 (SIGSPATIAL 2019), long paper, (acceptance rate: 21.7%), Chicago, Illinois, USA, accepted. This workshop will encourage researchers from interdisciplinary domains working on multi-modality and/or fact-checking to come together and work on multimodal (images, memes, videos etc.) ", ACM Transactions on Spatial Algorithms and Systems (TSAS), (Acceptance Rate: 11%), Volume 2 Issue 4, Acticle No. Introduction: SIGKDD aims to provide the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining.SIGKDD will encourage: basic research in KDD (through annual research conferences, newsletter and other related activities . ISPRS International Journal of Geo-Information (IJGI), (impact factor: 1.502), 5.10 (2016): 193. fact-checking. Maria Malik, Hassan Ghasemzadeh, Tinoosh Mohsenin, Rosario Cammarota, Liang Zhao, Avesta Sasan, Houman Homayoun, Setareh Rafatirad. December, 12-16, 2022. However, research in the AI field also shows that their performance in the wild is far from practical due to the lack of model efficiency and robustness towards open-world data and scenarios. The goal of the inaugural HC-SSL workshop is to highlight and facilitate discussions in this area and expose the attendees to emerging potentials of SSL for human-centric representation learning, and promote responsible AI within the context of SSL. of Graz), Cynthia Rudin (Duke Univ.) 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. For research track papers and applied data science track papers. iDetective: An Intelligent System for Automatic Identification of Key Actors in Online Hack Forums. Shiyu Wang, Xiaojie Guo, Liang Zhao. 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. Attendance is open to all. Following this AAAI conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. ACM Transactions on Spatial Algorithms and Systems (TSAS), 5, 3, Article 19 (September 2019), 28 pages. 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). Short or position papers of up to 4 pages are also welcome. VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. Submissions of technical papers can be up to 7 pages excluding references and appendices. Unsupervised Deep Subgraph Anomaly Detection. Its capabilities have expanded from processing structured data (e.g. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. The cookie is used to store the user consent for the cookies in the category "Analytics". Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Submission at:https://easychair.org/my/conference?conf=edsmls2022. Liang Zhao, Ting Hua, Chang-Tien Lu, and Ing-Ray Chen. 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 . 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." Deep Geometric Neural Networks for Spatial Interpolation. 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. 4, Roosevelt Rd., Taipei, TaiwanAffiliation: National Taiwan UniversityPhone: +1-412-465-0130Email: yvchen@csie.ntu.edu.tw, Paul CrookAddress: 1 Hacker Way, Menlo Park, CA, USAAffiliation: FacebookPhone: +1-650-885-0094Email: pacrook@fb.com, DSTC 10 home:https://dstc10.dstc.community/homeDSTC 10 CFPs:https://dstc10.dstc.community/calls_1/call-for-workshop-papers. By clicking Accept All, you consent to the use of ALL the cookies. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. The goal of this workshop is to offer an opportunity to appreciate the diversity in applications, to draw connections to inform decision optimization across different industries, and to discover new problems that are fundamental to marketplaces of different domains. Accelerated Gradient-free Neural Network Training by Multi-convex Alternating Optimization. Workshop Date: Sunday August 14, 2022 EDT. Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. Event Prediction in the Big Data Era: A Systematic Survey. 963-971, Apr-May 2015. ML-guided rare event modeling and system uncertainty quantification, Development of software, libraries, or benchmark datasets, and. How can we engineer trustable AI software architectures? Please use vds@ieeevis.org to get in touch with us, or follow us on Twitter at @VisualDataSci. [Best Paper Candidate]. 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. 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. 1-39, November 2016. Motif-guided Heterogeneous Graph Deep Generation. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. We also use third-party cookies that help us analyze and understand how you use this website. In addition, broad deployment of ML software in networked systems inevitably exposes ML software to attacks. Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. This manual extraction process is usually inefficient, error-prone, and inconsistent. The trustworthy issues of clinical AI methods were not discussed. 47, no. At least one author of each accepted submission must present the paper at the workshop. Representation Learning on Spatial Networks. 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. All the submissions should be anonymous. Frontiers in Big Data, accepted, 2021. Key obstacles include lack of high-quality data, difficulty in embedding complex scientific and engineering knowledge in learning, and the need for high-dimensional design space exploration under constrained budgets. 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. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). 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. Zheng Zhang and Liang Zhao. A 2-day workshop to share knowledge and research on five tracks of DSTC-10 and general related technical track. Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, and Chang-Tien Lu. The review process will be single blind. considered to be more practical and more related with real-world applications. Submission site:https://easychair.org/conferences/?conf=kdf22, Chair:Xiaomo Liu (J.P. Morgan Chase AI Research, xiaomo.liu@jpmchase.com), Zhiqiang Ma (J.P. Morgan Chase AI Research), Armineh Nourbakhsh (J.P. Morgan Chase AI Research), Sameena Shah (J.P. Morgan Chase AI Research), Gerard de Melo (Hasso Plattner Institute), Le Song (Mohamed bin Zayed University of Artificial Intelligence), Workshop URL:https://aaai-kdf.github.io/kdf2022/. 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. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 9.77%), to appear, 2022. This thread already has a best answer. Dynamic Tracking and Relative Ranking of Airport Threats from News and Social Media. The positive/negative social impacts and ethical issues related to adversarial ML. Knowledge and Information Systems (KAIS), (impact factor: 2.936), accepted. Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. The accepted papers will be allocated either a contributed talk or a poster presentation. The workshop follows a single-blind reviewing process. 689-698, Barcelona, Spain, Dec 2016. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. Graph Neural Networks: Foundations, Frontiers, and Applications. Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. Yuyang Gao, Giorgio Ascoli, Liang Zhao. TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints. Universit de MontralOffice of Admissions and RecruitmentC. Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. 2022. Accepted papers will be given the opportunity to present at the spotlight sessions during the workshop. Yuanqi Du*, Shiyu Wang* (co-first author), Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang, Aishwarya Varala, Abhinav Angirekula, Liang Zhao. Our goal is to build a stronger community of researchers exploring these methods, and to find synergies among these related approaches and alternatives. This cookie is set by GDPR Cookie Consent plugin. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. Conference stats are visualized below for a straightforward comparison. 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. Babies learn their first language through listening, talking, and interacting with adults. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. KDD 2022. Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior. 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. Neurocomputing (Impact Factor: 5.719), accepted. By registering, you agree to receive emails from UdeM. Submissions will be accepted via the Easychair submission website. ADMM for Efficient Deep Learning with Global Convergence. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. Full papers are allocated 20m presentation and 10m discussion. We hope to build upon that success. 2022. We expect ~60 attendees. Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad,. Three categories of contributions are sought: full-research papers up to 8 pages; short papers up to 4 pages; and posters and demos up to 2 pages. Note: The workshop is a collaboration between NASSMA organisation, Deepmind and UM6P. OARS-KDD2022: KDD 2022 Workshop on Online and Adaptive Recommender Systems Washington DC, DC, United States, August 15, 2022 Topics: data science artificial intelligence recommender system recommendation KDD 2022 Workshop on Online and Adaptive Recommender Systems (OARS) Call For Papers ================== Brave new ideas to learn AI models under bias and scarcity. Computer Science and Engineering, INESC-ID, IST Ulisboa, Lisbon, Portugal currently at Sorbonne University, Paris, France silvia.tulli@gaips.inesc-id.pt), Prashan Madumal (Science and Information Systems, University of Melbourne, Parkville, Australia pmathugama@student.unimelb.edu.au), Mark T. Keane (School of Computer Science, University College Dublin, Dublin, Ireland mark.keane@ucd.ie), David W. Aha (Navy Center for Applied Research in AI, Naval Research Laboratory, Washington, DC, USA david.aha@nrl.navy.mil), Adam Johns (Drexel University, Philadelphia, PA USA), Tathagata Chakraborti (IBM Research AI, Cambridge, MA USA), Kim Baraka (VU University Amsterdam, Netherlands), Isaac Lage (Harvard University, Cambridge, MA USA), David Martens (University of Antwerp, Belgium), Mohamed Chetouani (Sorbonne Universit, Paris, France), Peter Flach (University of Bristol, United Kingdom), Kacper Sokol (University of Bristol, United Kingdom), Ofra Amir (Technion, Haifa, Israel), Dimitrios Letsios (Kings College London, London, United Kingdom), Supplemental workshop site:https://sites.google.com/view/eaai-ws-2022/topic. STGEN: Deep Continuous-time Spatiotemporal Graph Generation. "How events unfold: spatiotemporal mining in social media." The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features. The workshop is being organized by application area or other, panels, invited speakers, interactive, small groups, discussions, presentations. In other words, many existing FL solutions are still exposed to various security and privacy threats. Submissions are limited to 4 pages, not including references. Each accepted paper presentation will be allocated between 15 and 20 minutes. Data mining systems and platforms, and their efficiency, scalability, security and privacy. 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 . Attendance is open to all, subject to any room occupancy constraints. and Simone Stumpf (Univ. For program deadlines, click on the Admissions and Regulations tab on the specific page of study. 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. ACM, 2014. Although textual data is prevalent in a large amount of finance-related business problems, we also encourage submissions of studies or applications pertinent to finance using other types of unstructured data such as financial transactions, sensors, mobile devices, satellites, social media, etc. Deadline: AI4science NASSMA 2022 2022 AI4science NASSMA 2022 '22 . Submissions will go through a double-blind review process. 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)^.
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