FL4Data-Mining@KDD 2023 : International Workshop on Federated Learning for Distributed Data Mining @ ACM SIGKDD Long Beach, California
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Event Date: | August 06, 2023 - August 10, 2023 |
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Abstract Submission Deadline: | May 23, 2023 |
Submission Deadline: | May 30, 2023 |
Notification of Acceptance: | June 23, 2023 |
Camera Ready Version Due: | July 20, 2023 |
Call for Papers |
By hosting this workshop at SIGKDD, we hope to promote the development of federated learning as a scientific field and encourage data mining researchers and practitioners to collaborate on this important research topic. We envision the workshop will bring in an overall advancement of FL and broaden its impact in the data mining research and industrial community, while FL has become an increasingly important tool for data mining in recent years. The workshop will cover the foundation and advanced problems in FL within the below three categories.
1. Scalability of FL facing heterogeneous data and heterogeneous computation or communication resources, including * Learning with a large scale of clients; * Learning from heterogeneous data distributions; * Learning from heterogeneous hardware or computation capabilities; * High-dimensional feature selection from distributed clients; * Learning under unreliable network conditions. 2. Trustworthiness. Problems and solutions for the security, privacy, and social alignment of FL systems, including * Privacy leakage during training and inference; * Uncertainty in data collection with noisy labels or data; * Backdoor attacks; * Data poisoning. 3. Applications. Explorations on novel research problems of FL and FL algorithms for real-world applications, including * Bioinformatics and biomedical informatics; * Financial engineering and quantitative finance; * Medical imaging; * Drug discovery; * Social networks and graph-based learning; * Natural language processing; * Computer vision. Moreover, we aim to attract high-quality original research of federated learning with applications, evaluation, and algorithms. We also plan to invite open discussions on controversial yet crucial topics regarding FL systems and discuss their barriers in data mining. Submission Guidelines We invite short technical papers - up to 5 pages including references and unlimited pages of appendix. All manuscripts should be submitted in a single PDF file including all content, figures, tables, and references, following the new Standard ACM Conference Proceedings Template. For LaTeX users: unzip acmart.zip, make, and use sample-sigconf.tex as a template; Additional information about formatting and style files is available online at ACM Proceedings Template (https://www.acm.org/publications/proceedings-template). Additionally, papers must be in the two-column format, with the recommended setting for Latex file: \documentclass[sigconf, review]{acmart}. Papers should be submitted to https://openreview.net/group?id=KDD.org/2023/Workshop/FL4Data-Mining All papers will be double-blinded and peer-reviewed by at least 2 reviewers. While all accepted papers will be presented with posters, high-quality accepted papers will also have the opportunity to participate in the oral/spotlight presentation and win our Best Paper Award(s). We will also present accepted papers on our website. According to the policy of the KDD conference, the accepted papers will NOT be included in proceedings or any form of publication. |
Summary |
FL4Data-Mining@KDD 2023 : International Workshop on Federated Learning for Distributed Data Mining @ ACM SIGKDD will take place in Long Beach, California. It’s a 5 days event starting on Aug 6, 2023 (Sunday) and will be winded up on Aug 10, 2023 (Thursday). FL4Data-Mining@KDD 2023 falls under the following areas: DATA MINING, FEDERATED LEARNING, DISTRIBUTED LEARNING, MACHINE LEARNING, etc. Submissions for this Workshop can be made by May 30, 2023. Authors can expect the result of submission by Jun 23, 2023. Upon acceptance, authors should submit the final version of the manuscript on or before Jul 20, 2023 to the official website of the Workshop. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the FL4Data-Mining@KDD 2023
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Credits and Sources |
[1] FL4Data-Mining@KDD 2023 : International Workshop on Federated Learning for Distributed Data Mining @ ACM SIGKDD |