49 citations · 235 across the 48 of their papers we have counts for
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stat.ML2022★ 2 cited
Learning to Optimize with Stochastic Dominance Constraints
Hanjun Dai, Yuan Xue, Niao He +4
In real-world decision-making, uncertainty is important yet difficult to handle. Stochastic dominance provides a theoretically sound approach for comparing uncertain quantities, bu…
stat.ML2020★ 49 cited
GenDICE: Generalized Offline Estimation of Stationary Values
Ruiyi Zhang, Bo Dai, Lihong Li +1
An important problem that arises in reinforcement learning and Monte Carlo methods is estimating quantities defined by the stationary distribution of a Markov chain. In many real-w…
stat.ML2018★ 3 cited
Variational Rejection Sampling
Aditya Grover, Ramki Gummadi, Miguel Lazaro-Gredilla +2
Learning latent variable models with stochastic variational inference is challenging when the approximate posterior is far from the true posterior, due to high variance in the grad…