4 papers
Near-Minimax-Optimal Rates for Asynchronous TD Learning with Markovian Data
Yang Peng
We study the last iterate of standard importance-weighted temporal-difference (TD) learning from a single trajectory of a finite Markov decision process. The trajectory follows a b…
Task-Resolved Fisher Spectroscopy for Quantum Reservoir Computing
Yang Peng
Quantum reservoir computing (QRC) uses fixed quantum dynamics to encode a time series and trains only a classical readout, but a benchmark capacity alone does not reveal whether ta…
Online Inference in Distributional Temporal-Difference Learning
Yang Peng, Liangyu Zhang
We study online statistical inference for functionals of the return distribution under a fixed policy. The return distribution is estimated by nonparametric distributional temporal…
Universal Neural Propagator: Learning Time Evolution in Many-Body Quantum Systems
Zihao Qi, Christopher Earls, Yang Peng
Conventional approaches to simulating quantum many-body dynamics produce a single trajectory: if the Hamiltonian or the initial state is changed, the computation must be re-perform…