26 citations · 58 across the 7 of their papers we have counts for
7 papers
A Convergence Theory for Federated Average: Beyond Smoothness
Xiaoxiao Li, Zhao Song, Runzhou Tao +1
Federated learning enables a large amount of edge computing devices to learn a model without data sharing jointly. As a leading algorithm in this setting, Federated Average FedAvg,…
Federated Adversarial Learning: A Framework with Convergence Analysis
Xiaoxiao Li, Zhao Song, Jiaming Yang
Federated learning (FL) is a trending training paradigm to utilize decentralized training data. FL allows clients to update model parameters locally for several epochs, then share…
Training Overparametrized Neural Networks in Sublinear Time
Yichuan Deng, Hang Hu, Zhao Song +2
The success of deep learning comes at a tremendous computational and energy cost, and the scalability of training massively overparametrized neural networks is becoming a real barr…
Smoothed Online Combinatorial Optimization Using Imperfect Predictions
Kai Wang, Zhao Song, Georgios Theocharous +1
Smoothed online combinatorial optimization considers a learner who repeatedly chooses a combinatorial decision to minimize an unknown changing cost function with a penalty on switc…
When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?
Simon S. Du, Wei Hu, Zhiyuan Li +3
Particle filtering is a popular method for inferring latent states in stochastic dynamical systems, whose theoretical properties have been well studied in machine learning and stat…
Efficient Model-free Reinforcement Learning in Metric Spaces
Zhao Song, Wen Sun
Model-free Reinforcement Learning (RL) algorithms such as Q-learning [Watkins, Dayan 92] have been widely used in practice and can achieve human level performance in applications s…
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective
Zhao Song, Ronald E. Parr, Lawrence Carin
The impact of softmax on the value function itself in reinforcement learning (RL) is often viewed as problematic because it leads to sub-optimal value (or Q) functions and interfer…