Summary of Mitigating Privacy Risk in Membership Inference by Convex-concave Loss, By Zhenlong Liu et al.
Mitigating Privacy Risk in Membership Inference by Convex-Concave Lossby Zhenlong Liu, Lei Feng, Huiping Zhuang,…
Mitigating Privacy Risk in Membership Inference by Convex-Concave Lossby Zhenlong Liu, Lei Feng, Huiping Zhuang,…
Implicit Diffusion: Efficient Optimization through Stochastic Samplingby Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel,…
Linearizing Models for Efficient yet Robust Private Inferenceby Sreetama Sarkar, Souvik Kundu, Peter A. BeerelFirst…
Multi-Timescale Ensemble Q-learning for Markov Decision Process Policy Optimizationby Talha Bozkus, Urbashi MitraFirst submitted to…
Differentially Private Deep Model-Based Reinforcement Learningby Alexandre Rio, Merwan Barlier, Igor Colin, Albert ThomasFirst submitted…
Asynchronous Diffusion Learning with Agent Subsampling and Local Updatesby Elsa Rizk, Kun Yuan, Ali H.…
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learningby Jialuo…
Flashback: Understanding and Mitigating Forgetting in Federated Learningby Mohammed Aljahdali, Ahmed M. Abdelmoniem, Marco Canini,…
Offline Actor-Critic Reinforcement Learning Scales to Large Modelsby Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang,…
Succinct Interaction-Aware Explanationsby Sascha Xu, Joscha Cüppers, Jilles VreekenFirst submitted to arxiv on: 8 Feb…