Asia
SHE: A Fast and Accurate Deep Neural Network for Encrypted Data
Neural Information Processing Systems http://nips.cc/
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning
Bregman divergence for greater adaptability in personalized scenarios.
Total stochastic gradient algorithms and applications in reinforcement learning
Neural Information Processing Systems http://nips.cc/
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity
This is, e.g., the typical setting of many ERM
Maximum-Entropy Fine Grained Classification
Abhimanyu Dubey, Otkrist Gupta, Ramesh Raskar, Nikhil Naik
Neural Information Processing Systems http://nips.cc/
Streaming Bayesian Inference for Crowdsourced Classification
Edoardo Manino, Long Tran-Thanh, Nicholas Jennings
Neural Information Processing Systems http://nips.cc/
Near-OptimalRegretforAdversarialMDPwith DelayedBanditFeedback
The standard assumption in reinforcement learning (RL) is that agents observe feedback for their actions immediately. However, in practice feedback is often observedindelay.