Search Results for author: Feicheng Wang

Found 3 papers, 2 papers with code

Rate-matching the regret lower-bound in the linear quadratic regulator with unknown dynamics

no code implementations11 Feb 2022 Feicheng Wang, Lucas Janson

The linear quadratic regulator with unknown dynamics is a fundamental reinforcement learning setting with significant structure in its dynamics and cost function, yet even in this setting there is a gap between the best known regret lower-bound of $\Omega_p(\sqrt{T})$ and the best known upper-bound of $O_p(\sqrt{T}\,\text{polylog}(T))$.

reinforcement-learning Reinforcement Learning (RL)

Exact Asymptotics for Linear Quadratic Adaptive Control

2 code implementations2 Nov 2020 Feicheng Wang, Lucas Janson

Recent progress in reinforcement learning has led to remarkable performance in a range of applications, but its deployment in high-stakes settings remains quite rare.

reinforcement-learning Reinforcement Learning (RL)

The Expressive Power of Neural Networks: A View from the Width

1 code implementation NeurIPS 2017 Zhou Lu, Hongming Pu, Feicheng Wang, Zhiqiang Hu, Li-Wei Wang

That is, there are classes of deep networks which cannot be realized by any shallow network whose size is no more than an exponential bound.

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