Summary of Learning Robust and Privacy-preserving Representations Via Information Theory, by Binghui Zhang et al.
Learning Robust and Privacy-Preserving Representations via Information Theoryby Binghui Zhang, Sayedeh Leila Noorbakhsh, Yun Dong,…
Learning Robust and Privacy-Preserving Representations via Information Theoryby Binghui Zhang, Sayedeh Leila Noorbakhsh, Yun Dong,…
Navigating Towards Fairness with Data Selectionby Yixuan Zhang, Zhidong Li, Yang Wang, Fang Chen, Xuhui…
Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Modelby Yujun Li, Hongyuan Zhang, Yuan YuanFirst…
Paid with Models: Optimal Contract Design for Collaborative Machine Learningby Bingchen Wang, Zhaoxuan Wu, Fusheng…
Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literatureby Sijia…
Progressive Compression with Universally Quantized Diffusion Modelsby Yibo Yang, Justus C. Will, Stephan MandtFirst submitted…
SegHeD+: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints and Lesion-aware Augmentationby…
PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimizationby Mingjing Xu, Peizhong Ju, Jia Liu,…
Optimal Rates for Robust Stochastic Convex Optimizationby Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J.…
Understanding and Mitigating Memorization in Diffusion Models for Tabular Databy Zhengyu Fang, Zhimeng Jiang, Huiyuan…