27 citations · 98 across the 12 of their papers we have counts for
4 papers · 1 filter
Model Selection in Batch Policy Optimization
Jonathan N. Lee, George Tucker, Ofir Nachum +1
We study the problem of model selection in batch policy optimization: given a fixed, partial-feedback dataset and model classes, learn a policy with performance that is competi…
Learning from Conditional Distributions via Dual Embeddings
Bo Dai, Niao He, Yunpeng Pan +2
Many machine learning tasks, such as learning with invariance and policy evaluation in reinforcement learning, can be characterized as problems of learning from conditional distrib…
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization
Gang Niu, Bo Dai, Makoto Yamada +1
We propose a general information-theoretic approach called Seraph (SEmi-supervised metRic leArning Paradigm with Hyper-sparsity) for metric learning that does not rely upon the man…
EigenGP: Sparse Gaussian process models with data-dependent eigenfunctions
Yuan Qi, Bo Dai, Yao Zhu
Gaussian processes (GPs) provide a nonparametric representation of functions. However, classical GP inference suffers from high computational cost and it is difficult to design non…