CoLiDR: Concept Learning using Aggregated Disentangled Representations
Comments KDD 2024
期刊&会议
ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 会议 · Data Mining
Comments KDD 2024
Comments Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Comments To be published in the 2nd Workshop on Causal Inference and Machine Learning in Practice, KDD 2024, August 25 to 29, 2024, Barcelona, Spain, 10 pages
Comments KDD MLF Workshop 2024. Dataset can be accessed at http://elliptic.co/elliptic2. Code can be accessed at https://github.com/MITIBMxGraph/Elliptic2
Comments EAI-KDD'2024. Code at https://github.com/qiulingxu/POSIT
Comments In KDD'24; with full appendix
Journal ref KDD 2024
Comments To appear in KDD 2024 (survey paper). The typo in Equation (5) has been fixed
Comments 12 pages, 4 figures, To Appear in KDD 2024
Comments Accepted by KDD'24 (Research Track)
Comments Accepted by KDD 2024
Comments To be published in KDD 2024
Comments Abstract presentation at BIOKDD@ACM KDD 2024
Comments Accepted by KDD 2024
Comments Accepted by KDD 2024
Comments Accepted to KDD'24
Comments 8 pages, 10 figures, KDD 2024 Workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth
Comments KDD 2024
Comments Accepted by KDD 2024
Comments 30th SIGKDD Conference on Knowledge Discovery and Data Mining
Comments ACM SIGKDD 2024
Comments 8 pages, Accepted at KDD 2024
Comments Accepted by KDD 2024
Comments Accepted by KDD 2024
Comments Survey Article for the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2024) Tutorial
Journal ref Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)
Comments Accepted by SIGKDD 2024, research track
Comments 12 pages, to be published at KiL'24: Workshop on Knowledge-infused Learning co-located with 30th ACM KDD Conference, August 26, 2024, Barcelona, Spain
Comments Published as a conference paper at KDD 2024
Comments KDD 2024
Comments Accepted at KDD 2024 Research Track, codes will be available at https://github.com/jyansir/tmlp