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. Qiang Yang, Hong Kong University of Science and Technology/ WeBank, China, (qyang@cse.ust.hk ), Sin G. Teo, Institute for Infocomm Research, Singapore (teosg@i2r.a-star.edu.sg), Han Yu, Nanyang Technological University, Singapore (han.yu@ntu.edu.sg), Lixin Fan, WeBank, China (lixinfan@webank.com), Chao Jin, Institute for Infocomm Research, Singapore (jin_chao@i2r.a-star.edu.sg), Le Zhang, University of Electronic Science and Technology of China (zhangleuestc@gmail.com), Yang Liu, Tsinghua University, China (liuy03@air.tsinghua.edu.cn), Zengxiang Li, Digital Research Institute, ENN Group, China (lizengxiang@enn.cn), Workshop site:http://federated-learning.org/fl-aaai-2022/. ICONF VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. Full (8 pages) and short (4 pages, work in progress) papers, AAAI style. The accelerated developments in the field of Artificial Intelligence (AI) hint at the need for considering Safety as a design principle rather than an option. Chen Ling, Carl Yang, Liang Zhao. 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. Disease Contact Network. text, images, and videos). IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Online marketplaces exist in a diverse set of domains and industries, for example, rideshare (Lyft, DiDi, Uber), house rental (Airbnb), real estate (Beke), online retail (Amazon, Ebay), job search (LinkedIn, Indeed.com, CareerBuilder), and food ordering and delivery (Doordash, Meituan). Xiaojie Guo, Yuanqi Du, Liang Zhao. 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. Papers will be peer-reviewed and selected for oral and/or poster presentations at the workshop. Options include pruning a trained network or training many networks automatically. Advances in complex engineering systems such as manufacturing and materials synthesis increasingly seek artificial intelligence/machine learning (AI/ML) solutions to enhance their design, development, and production processes. 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. Interpretable Molecular Graph Generation via Monotonic Constraints. Deep Spatial Domain Generalization. The consideration and experience of adversarial ML from industry and policy making. "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. 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. 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/. 2022. Panel discussion: Interactive Q&A session with a panel of leading researchers. Accepted papers will be given the opportunity to present at the spotlight sessions during the workshop. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. 2999-3006, New Orleans, US, Feb 2018. The extraction, representation, and sharing of health data, patient preference elicitation, personalization of generic therapy plans, adaptation to care environments and available health expertise, and making medical information accessible to patients are some of the relevant problems in need of AI-based solutions. Declarative languages and differentiable programming. Han Wang, Hossein Sayadi, Avesta Sasan, Houman Homayoun, Liang Zhao, Tinoosh Mohsenin, Setareh Rafatirad. Position papers (4 pages in length for main content + 2 pages for references in AAAI format): we are seeking position papers that advocate for a particular approach or set of approaches, or present an overview of a promising relevant research area. fact-checking. The cookie is used to store the user consent for the cookies in the category "Analytics". A Report on the First Workshop on Document Intelligence (DI) at NeurIPS 2019. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph. At least one author of each accepted submission must register and present their paper at the workshop. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Xiaosheng Li, Jessica Lin, and Liang Zhao. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Submissions should follow the AAAI-2022https://aaai.org/Conferences/AAAI-22/aaai22call/. Conference Management Toolkit - Login 2022. November 11-17, 2023. Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, Shouhuai Xu. Proceedings of the IEEE (impact factor: 9.237), vol. 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. This cookie is set by GDPR Cookie Consent plugin. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. If these formalities are not completed in time, you will have to file a new application at a later date. The submission website ishttps://cmt3.research.microsoft.com/TAIH2022. 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. Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. 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. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2014), industrial track, pp. Submission site:https://cmt3.research.microsoft.com/ITCI2022, Murat Kocaoglu, Chair (Purdue University, mkocaoglu@purdue.edu), Negar Kiyavash (EPFL, negar.kiyavash@epfl.ch), Todd Coleman (UCSD, tpcoleman@ucsd.edu), Supplemental workshop site:https://sites.google.com/view/itci22. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is Algorithms and theories for learning AI models under bias and scarcity. Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, and Chang-Tien Lu. 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. 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 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. Hierarchical Incomplete Multisource Feature Learning for Spatiotemporal Event Forecasting. in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), research track (acceptance rate: 18.2%), San Francisco, California, pp. Deep Graph Transformation for Attributed, Directed, and Signed Networks. [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. 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/. ICDM: International Conference on Data Mining 2024 2023 2022 - WikiCFP upon methodologies and applications for extracting useful knowledge from data [1]. Identification of key challenges and opportunities for future research. The advances in web science and technology for data management, integration, mining, classification, filtering, and visualization has given rise to a variety of applications representing real-time data on epidemics. Yuyang Gao, Giorgio Ascoli, Liang Zhao. Short papers 10m presentation and 5m discussion. Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, and Liang Zhao. Send this CFP to us by mail: cfp@ourglocal.org. Integration of AI-based approaches with engineering prototyping and manufacturing. We invite the submission of papers with 4-6 pages. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016), regular paper, (acceptance rate: 8.5%), pp. The goal of ITCI22 is to bring together researchers working at the intersection of information theory, causal inference and machine learning in order to foster new collaborations and provide a venue to brainstorm new ideas, exemplify to the information theory community causal inference and discovery as an application area and highlight important technical challenges motivated by practical ML problems, draw the attention of the wider machine learning community to the problems at the intersection of causal inference and information theory, and demonstrate to the community the utility of information-theoretic tools to tackle causal ML problems. Please use ACM Conference templates (two column format). Factorized Deep Generative Models for End-to-End Trajectory Generation with Spatiotemporal Validity Constraints. 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. ), Programs also suitable for students not fluent in French, Information and Communication Technologies, Graduate (master's, specialized graduate diploma (DESS), microprogram): February 1, Graduate (master's, specialized graduate diploma (DESS), microprogram): September 1. We solicit papers describing significant and innovative research and applications to the field of job marketplaces. The workshop will include several technical sessions, a virtual poster session where presenters can discuss their work, to further foster collaborations, multiple invited speakers covering crucial aspects for the practical deep learning in the wild, especially the efficient and robust deep learning, some tutorial talks, the challenge for efficient deep learning and solution presentations, and will conclude with a panel discussion. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. 4498-4505, New Orleans, US, Feb 2018. Deep Multi-attributed Graph Translation with Node-Edge Co-evolution. 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. Yuyang Gao, Giorgio Ascoli, Liang Zhao. Yanfang Ye, Yiming Zhang, Yujie Fan, Chuan Shi and Liang Zhao. 25, 2022: We have announced Call for Nominations: , Mar. We will include a panel discussion to close the workshop, in which the audience can ask follow up questions and to identify the key AI challenges to push the frontiers in Chemistry. 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. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. 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! All the submissions must follow the AAAI-22 formatting guidelines, camera-ready style. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). of London). Paper Submission Deadline: 23:59 on Thursday. In particular, we encourage papers covering late-breaking results and work-in-progress research. Self-supervised learning (SSL) has shown great promise in problems involving natural language and vision modalities. ", ACM Transactions on Spatial Algorithms and Systems (TSAS), (Acceptance Rate: 11%), Volume 2 Issue 4, Acticle No. 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. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Because of the time needed to complete the formalities for entering Canada and Quebec, the admission period for international applicants ends several weeks before the session begins. sup-port vector machine (SVM), decision tree, random forest, etc.) 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. Temporal Domain Generalization with Drift-Aware Dynamic Neural Network. 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. Oral Paper (Top 5% among the accepted papers). ), Learning with algebraic or combinatorial structure, Link analysis/prediction, node classification, graph classification, clustering for complex graph structures, Theoretical analysis of graph algorithms or models, Optimization methods for graphs/manifolds, Probabilistic and graphical models for structured data, Unsupervised graph/manifold embedding methods. Guangji Bai and Liang Zhao. Securing personal information, genomics, and intellectual property, Adversarial attacks and defenses on biomedical datasets, Detecting and preventing spread of misinformation, Usable security and privacy for digital health information, Phishing and other attacks using health information, Novel use of biometrics to enhance security, Machine learning (including RL) security and resiliency, Automation of data labeling and ML techniques, Operational and commercial applications of AI, Explanations of security decisions and vulnerability of explanations. While progress has been impressive, we believe we have just scratched the surface of what is capable, and much work remains to be done in order to truly understand the algorithms and learning processes within these environments. Reasons include: (1) a lack of certification of AI for security, (2) a lack of formal study of the implications of practical constraints (e.g., power, memory, storage) for AI systems in the cyber domain, (3) known vulnerabilities such as evasion, poisoning attacks, (4) lack of meaningful explanations for security analysts, and (5) lack of analyst trust in AI solutions. Neurocomputing (Impact Factor: 5.719), accepted. ADMM for Efficient Deep Learning with Global Convergence. 205-214, San Francisco, California, Aug 2016. Hua, Ting, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. "Multi-resolution Spatial Event Forecasting in Social Media." PLOS ONE (impact factor: 3.534), vo. 11, 2022: We have posted the list of accepted Workshops at, Apr. The PAKDD is one of the longest established and leading international conferences in the areas of data mining and knowledge discovery.