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05/04/2023
FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization
Federated learning is an important framework in modern machine learning ...
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10/14/2022
Continuous-in-time Limit for Bayesian Bandits
This paper revisits the bandit problem in the Bayesian setting. The Baye...
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12/02/2021
On Large Batch Training and Sharp Minima: A Fokker-Planck Perspective
We study the statistical properties of the dynamic trajectory of stochas...
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10/25/2021
Operator Augmentation for Model-based Policy Evaluation
In model-based reinforcement learning, the transition matrix and reward ...
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08/03/2021
Variational Actor-Critic Algorithms
We introduce a class of variational actor-critic algorithms based on a v...
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09/28/2020
Why resampling outperforms reweighting for correcting sampling bias
A data set sampled from a certain population is biased if the subgroups ...
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06/11/2020
Borrowing From the Future: Addressing Double Sampling in Model-free Control
In model-free reinforcement learning, the temporal difference method and...
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01/24/2020
A Sharp Convergence Rate for the Asynchronous Stochastic Gradient Descent
We give a sharp convergence rate for the asynchronous stochastic gradien...
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12/01/2019
Borrowing From the Future: An Attempt to Address Double Sampling
For model-free reinforcement learning, the main difficulty of stochastic...
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10/26/2019
The Vlasov-Fokker-Planck Equation with High Dimensional Parametric Forcing Term
We consider the Vlasov-Fokker-Planck equation with random electric field...
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10/16/2019
An Uncertainty Quantification Approach to the Study of Gene Expression Robustness
We study a chemical kinetic system with uncertainty modeling a gene regu...
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12/03/2018