A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learningby Xiaojin Zhang, Mingcong Xu,…
Fair Submodular Coverby Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. CrawfordFirst submitted to arxiv…
Amazing Things Come From Having Many Good Modelsby Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo…
Introducing ‘Inside’ Out of Distributionby Teddy LazebnikFirst submitted to arxiv on: 5 Jul 2024CategoriesMain: Machine…
Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directionsby Shumaila Javaid,…
Remembering Everything Makes You Vulnerable: A Limelight on Machine Unlearning for Personalized Healthcare Sectorby Ahan…
Learning to (Learn at Test Time): RNNs with Expressive Hidden Statesby Yu Sun, Xinhao Li,…
Regulating Model Reliance on Non-Robust Features by Smoothing Input Marginal Densityby Peiyu Yang, Naveed Akhtar,…
KAN-ODEs: Kolmogorov-Arnold Network Ordinary Differential Equations for Learning Dynamical Systems and Hidden Physicsby Benjamin C.…
Meta-Learning and representation learner: A short theoretical noteby Mouad El BouchattaouiFirst submitted to arxiv on:…