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stat.ML2021
Accelerated and instance-optimal policy evaluation with linear function approximation
Tianjiao Li, Guanghui Lan, Ashwin Pananjady
We study the problem of policy evaluation with linear function approximation and present efficient and practical algorithms that come with strong optimality guarantees. We begin by…
stat.ML2018★ 7 cited
Optimal Adaptive and Accelerated Stochastic Gradient Descent
Qi Deng, Yi Cheng, Guanghui Lan
Stochastic gradient descent (\textsc{Sgd}) methods are the most powerful optimization tools in training machine learning and deep learning models. Moreover, acceleration (a.k.a. mo…