a concise checklist by Prof. Eamonn Keogh (UC Riverside). Attendance is open to any interested participants at AAAI-22. ML-guided rare event modeling and system uncertainty quantification, Development of software, libraries, or benchmark datasets, and. Welcome to DLG-KDD'22! - Bitbucket Checklist for Revising a SIGKDD Data Mining Paper, How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering, https://researcher.watson.ibm.com/researcher/view_group.php?id=144, IEEE International Conference on Big Data (, AAAI Conference on Artificial Intelligence (, IEEE International Conference on Data Engineering (, SIAM International Conference on Data Mining (, Pacific-Asia Conference on Knowledge Discovery and Data Mining (, ACM SIGKDD International Conference on Knowledge discovery and data mining (, European Conference on Machine learning and knowledge discovery in databases (, ACM International Conference on Information and Knowledge Management (, IEEE International Conference on Data Mining (, ACM International Conference on Web Search and Data Mining (, 18.4% (181/983, research track), 22.5% (112/497, applied data science track), 59.1% (107/181, research track), 35.7% (40/112, applied data science track), 17.4% (130/748, research track), 22.0% (86/390, applied data science track), 49.2% (64/130, research track), 41.9% (36/86, applied data science track), 18.1% (142/784, research track), 19.9% (66/331, applied data science track), 49.3% (70/142, research track), 60.1% (40/66, applied data science track), 18.5% (194/1046, overall), 9.1% (95/?, regular paper), ?% (99/?, short paper), 19.8% (188/948, overall), 8.9% (84/?, regular paper), ?% (104/?, short paper), 19.9% (155/778, overall), 9.3% (72/?, regular paper), ?% (83/?, short paper), 19.6% (178/904, overall), 8.6% (78/?, regular paper), ?% (100/?, short paper), 19.6% (202/1031, long paper), 22.7% (107/471, short paper), 21.8% (38/174m applied research), 17% (147/826, long paper), 23% (96/413, short paper), 25% (demo), 34% (industry paper), Short papers are presented at poster sessions, 20% (171/855, long paper), 28% (119/419, short paper), 38% (30/80, demo paper), 23% (160/701, long paper), 24% (55/234, short paper), 54 extended short papers (6 pages), 26% (94/354, research track), 26% (37/143, applied ds track), 15% (23/151, journal track), 27.8% (164/592, overall), 9.8% (58/592, long presentation), 18.1% (107/592, regular), 28.2% (129/458, overall), 9.8% (45/458, long presentation), 18.3% (84/458, regular), 29.6% (91/307, overall), 12.7% (39/307, long presentation), 16.9% (52/307, regular), 40.4% (34/84, long presentation), 59.5% (50/84, short presentation)^, 16.3% (84/514 in which 3 papers are withdrawn/rejected after the acceptance), 28.4% (23/81, long presentation), 71.6% (58/81, short presentation)^, 30% (24/80, long presentation), 70% (56/80, short presentation)^, 29.8% (20/67, long presentation), 70.2% (47/67, short presentation)^, 53.8% (21/39, long presentation), 46.2% (18/39, short presentation)^. The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. AI Conference Deadlines The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. Tips for Doing Good DM Research & Get it Published! 4 pages), and position (max. 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. In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. Interpretable Deep Graph Generation with Node-edge Codisentanglement. Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. 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. Zirui Xu, Fuxun Xu, Liang Zhao, and Xiang Chen. Template guidelines are here:https://www.acm.org/publications/proceedings-template. December 2020, July 21: Clarified that the workshop this year will be held, June 20: Paper notification is now extended to, Paper reviews are underway! Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. 47, no. Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/ADAM, Aarti Singh (Carnegie Mellon University), Baskar Ganapathysubramanian (ISU), Chinmay Hegde (New York University; contact: chinmay.h@nyu.edu), Mark Fuge (University of Maryland), Olga Wodo (University of Buffalo), Payel Das (IBM), Soumalya Sarkar (Raytheon), Workshop website:https://adam-aaai2022.github.io/. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. Data Mining Conference Acceptance Rate. These submissions would benefit from additional exposure and discussion that can shape a better future publication. 41-50, New Orleans, US, Dec 2017. 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. November 11-17, 2023. The 33rd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databasesg (ECML-PKDD 2022) (Acceptance Rate: 26%), accepted, 2022. Please refer to the KDD 2022 website for the policies of Conflict of Interest, Violations of Originality, and Dual Submission: A Best Paper Award will be presented to the best full paper as voted by the reviewers. Innovation, Service, and Rising Star Awards. In nearly all applications, reliability, safety, and security of such systems is a critical consideration. IEEE, 2014. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). 10 (2014): e110206. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. Algorithms and theories for explainable and interpretable AI models. Online. 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 ================== Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. [materials][data]. 15, pp. Online . Detailed information could be found on the website of the workshop. 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. All submissions must be anonymous and conform to AAAI standard for double-blind review. Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang. International Journal of Digital Earth, (impact factor: 3.097), 25 Aug 2020, https://doi.org/10.1080/17538947.2020.1809723. 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/. . 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/. Submissions will be peer reviewed, single-blinded. the 56th Design Automation Conference (DAC 2019), accepted, (acceptance rate: 20%), Las Vegas, US, 2019. Optimal transport theory, including statistical and geometric aspects; Gromov-Wasserstein distance and its variants; Bayesian inference for/with optimal transport; Gromovization of machine learning methods; Optimal transport-based generative modeling. KDD 2022 KDD . Furthermore, DNNs are data greedy in the context of supervised learning, and not well developed for limited label learning, for instance for semi-supervised learning, self-supervised learning, or unsupervised learning. 1, Sec. Recent years have witnessed growing efforts from the AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in education. NOTE: May 19: Notification. In addition to the keynote and presentations of accepted works, the workshop will include both a general discussion session on defining and addressing the key challenges in this area , and a lightning tutorial session that will include brief overviews and demos of relevant tools, including open source frameworks such as Ecole. We are in a conversation with some publishers once they confirm, we will announce accordingly. AAAI-22 Workshop Program - AAAI Three specific roles are part of this format: session chairs, presenters and paper discussants. "STED: semi-supervised targeted-interest event detectionin in twitter." 205-214, San Francisco, California, Aug 2016. This workshop aims to bring together FL researchers and practitioners to address the additional security and privacy threats and challenges in FL to make its mass adoption and widespread acceptance in the community. In Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. 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.) Novel mechanisms for eliciting and consuming user feedback, recommender, structured and generative models, concept acquisition, data processing, optimization; HCI and visualization challenges; Analysis of human factors/cognition and user modelling; Design, testing and assessment of IML systems; Studies on risks of interaction mechanisms, e.g., information leakage and bias; Business use cases and 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/. An Invertible Graph Diffusion Model for Source Localization. NOTE: Mandatory abstract deadline: 2022-08-08 Deadline: AAAI 157. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. Manuscripts must be submitted as PDF files viaEasyChair online submission system. Consult the list of programs available in the next session. https://doi.org/10.1007/s10707-019-00376-9. While we are planning an in-person workshop to be held at AAAI-22, we aim to accommodate attendees who may not be able to travel to Vancouver by allowing participation via live virtual invited talks and virtual poster sessions. The PAKDD is one of the longest established and leading international conferences in the areas of data mining and knowledge discovery. The AAAI template https://aaai.org/Conferences/AAAI-22/aaai22call/ should be used for all submissions. anomaly detection, and ensemble learning. Toward Model Parallelism for Deep Neural Network based on Gradient-free ADMM Framework. 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 . This topic encompasses forms of Neural Architecture Search (NAS) in which the performance properties of each architecture, after some training, are used to guide the selection of the next architecture to be tried. Through invited talks and presentations by the participants, this workshop will bring together current advances in Network Science as well as Machine Learning, and set the stage for continuing interdisciplinary research discussions. The 21st Web Conference (WWW 2022), (Acceptance Rate: 17.7%), accepted. Please note that the KDD Cup workshop will have no proceedings and the authors retain full rights to submit or post the paper at any other venue. Fuxun Yu, Zhuwei Qin, Chenchen Liu, Liang Zhao, Yanzhi Wang, Xiang Chen. For research track papers and applied data science track papers. VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. This workshop aims to bring together researchers from AI and diverse science/engineering communities to achieve the following goals: 1) Identify and understand the challenges in applying AI to specific science and engineering problems2) Develop, adapt, and refine AI tools for novel problem settings and challenges3) Community-building and education to encourage collaboration between AI researchers and domain area experts. We expect ~60 attendees. Submission Site:https://cmt3.research.microsoft.com/SAS2022, Abdelrahman Mohamed (Facebook, abdo@fb.com), Hung-yi Lee (NTU, hungyilee@ntu.edu.tw), Shinji Watanabe (CMU, shinjiw@ieee.org), Tara Sainath (Google, tsainath@google.com), Karen Livescu (TTIC, klivescu@ttic.edu), Shang-Wen Li (Facebook, shangwel@fb.com), Ewan Dunbar (University of Toronto, ewan.dunbar@utoronto.ca) Emmanuel Dupoux (EHESS/Facebook, dpx@fb.com), Workshop URL:https://aaai-sas-2022.github.io/. 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. At least three research trends are informing insights in this field. Trade-Off between Privacy-Preserving and Explainable Federated Learning Federated Learning Multi-Party Computation, Federated Learning Homomorphic Encryption, Federated Learning Personalization Techniques, Federated Learning Meets Mean-Field Game Theory, Federated Learning-based Corporate Social Responsibility. The trustworthy issues of clinical AI methods were not discussed. Identification of information-theoretic quantities relevant for causal inference and discovery. We will also organize 3 shared tasks in this workshop: punctuation restoration, domain adaptation for punctuation restoration, and chitchat detection. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. Please refer and submit through theLearning Network Architecture During Trainingworkshop website, which has more detailed information. Journal of Biomedical Semantics, (impact factor: 1.845), 2018, accepted. . 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. Connor Coley, Massachusetts Institute of TechnologyProf. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. The workshop is organized by paper presentations.The length of the workshop: 1-day, 6-8 pages for full papers2-4 for poster/short/position papers, Submission URL:https://easychair.org/conferences/?conf=aaai-2022-workshop, Wenzhong Guo (Fuzhou University, fzugwz@163.com), Chin-Chen Chang (Feng Chia University, alan3c@gmail.com), Chi-Hua Chen (Fuzhou University, chihua0826@gmail.com), Haishuai Wang (Fairfield University & Harvard University, hwang@fairfield.edu), Feng-Jang Hwang (University of Technology Sydney), Cheng Shi (Xian University of Technology), Ching-Chun Chang (National Institute of Informatics, Japan). CS Conference Deadlines - Yanlin Contrast Pattern Mining in Paired Multivariate Time Series of Controlled Driving Behavior Experiment. Why did so many AI/ML models fail during the pandemic? 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. 1-11, Feb 2016. The cookies is used to store the user consent for the cookies in the category "Necessary". Oilers Outperform Division Rivals at 2023 Trade Deadline Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. The post-lunch session will feature a second keynote talk, two invited talks. Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. We invite submissions of full papers, as well as works-in-progress, position papers, and papers describing open problems and challenges. It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. 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. ACM, 2013. 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/. 639-648, Nov 2015. 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 in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), short paper (acceptance rate: 19.9%), Singapore, Dec 2018, accepted. Following this AAAI conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. Invited speakers, panels, poster sessions, and presentations. Xiaosheng Li, Jessica Lin, Liang Zhao. Deep Spatial Domain Generalization. This workshop brings together researchers from diverse backgrounds with different perspectives to discuss languages, formalisms and representations that are appropriate for combining learning and reasoning. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. Liang Gou, Bosch Research (IEEE VIS liaison), Claudia Plant, University of Vienna (KDD liaison), Alvitta Ottley, Washington University, St. Louis, Junming Shao, University of Electronic Science and Technology of China, Visualization in Data Science (VDS at ACM KDD and IEEE VIS), Visualization in Data Science (VDS at ACM KDD and IEEE VIS). KDD 2022. Advances in AI technology, particularly perception and planning, have enabled unprecedented advances in autonomy, with autonomous systems playing an increasingly important role in day-to-day lives, with applications including IoT, drones, and autonomous vehicles. We will also have a video component for remote participation. 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. Welcome to the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2022), which will be held in Chengdu, China on May 16-19, 2022. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. Question answering on business documents. 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. 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. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. 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. Attendance is open to all prior registration to the workshop/conference. 105, no. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. The submission website ishttps://cmt3.research.microsoft.com/OTSDM2022. This date takes priority over those shown below and could be extended for some programs. 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. Previous healthcare-related workshops focus on how to develop AI methods to improve the accuracy and efficiency of clinical decision-making, including diagnosis, treatment, triage. Deep Generative Model for Periodic Graphs. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. We expect 50-65 people in the workshop. Frontiers in Big Data, accepted, 2021. Whats more, various AI based models are trained on massive student behavioral and exercise data to have the ability to take note of a students strengths and weaknesses, identifying where they may be struggling. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. How to do good research, Get it published in SIGKDD and get it cited! Submissions will go through a double-blind review process. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. If you are interested, please send a short email to rl4edorg@gmail.com and we can add you to the invitee list. Mingxuan Ju, Wei Song, Shiyu Sun, Yanfang Ye, Yujie Fan, Shifu Hou, Kenneth Loparo, and Liang Zhao. Information extraction and information retrieval for scientific documents; Question answering and question generation for scholarly documents; Word sense disambiguation, acronym identification and expansion, and definition extraction; Document summarization, text mining, document topic classification, and machine reading comprehension for scientific documents; Graph analysis applications including knowledge graph construction and representation, graph reasoning and query knowledge graphs; Biomedical image processing, scientific image plagiarism detection, and data visualization; Code/Pseudo-code generation from text and im-age/diagram captioning, New language understanding resources such as new syn-tactic/semantic parsers, language models or techniques to encode scholarly text; Survey or analysis papers on scientific document under-standing and new tasks and challenges related to each scientific domain; Factuality, data verification, and anti-science detection. ETA (expected time-of-arrival) prediction. Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market. Chen Ling, Carl Yang, Liang Zhao. ML4OR will serve as an interdisciplinary forum for researchers in both fields to discuss technical issues at this interface and present ML approaches that apply to basic OR building blocks (e.g., integer programming solvers) or specific applications. Geoinformatica, (impact factor: 2.392), Volume 20, Issue 4, pp 765-795, Oct 2016. Deep Geometric Neural Networks for Spatial Interpolation. How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. We would especially like to highlight approaches that are qualitatively different from some popular but computationally intensive NAS methods. We expect 50~75 participants and potentially more according to our past experiences. [Bests of ICDM]. Knowledge Discovery and Data Mining. Each paper will be reviewed by three reviewers in double-blind. Novel methods to learn from scarce/sparse, or heterogenous, or multimodal data. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. Integration of non-differentiable optimization models in learning. Big data Journal (impact factor: 1.489), vo. SIGKDD Explorations, Vol. While most work on XAI has focused on opaque learned models, this workshop also highlights the need for interactive AI-enabled agents to explain their decisions and models. The AAAI author kit can be downloaded from:https://www.aaai.org/Publications/Templates/AuthorKit22.zip. Novel approaches and works in progress are encouraged. We will instead host the accepted papers on this website (https://aka.ms/di-2022) indefinitely. Adverse event detection by integrating Twitter data and VAERS. We expect 60-70 participants. References will not count towards the page limit. Registration in each workshop is required by all active participants, and is also open to all interested individuals. Junxiang Wang, Yuyang Gao, Andreas Zufle, Jingyuan Yang, and Liang Zhao. As for the Kraken, they made one trade a month ago to acquire a seventh defenceman, Jaycob Megna and did nothing else (from 'Kraken remain quiet as NHL trade deadline passes,' The Seattle . Papers will be peer-reviewed by the Program Committee (2-3 reviewers per paper). Submission URL:https://easychair.org/my/conference?conf=vtuaaai2022. This 1-day workshop will include a mixture of invited speakers, panels (including discussion with the audience), and presentations from authors of accepted submissions.
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