37 citations · 43 across the 5 of their papers we have counts for
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stat.ML2020
GO Hessian for Expectation-Based Objectives
Yulai Cong, Miaoyun Zhao, Jianqiao Li +2
An unbiased low-variance gradient estimator, termed GO gradient, was proposed recently for expectation-based objectives $\mathbb{E}_{q_{\boldsymbolγ}(\boldsymbol{y})} [f(\boldsymbo…
stat.ML2019★ 4 cited
GO Gradient for Expectation-Based Objectives
Yulai Cong, Miaoyun Zhao, Ke Bai +1
Within many machine learning algorithms, a fundamental problem concerns efficient calculation of an unbiased gradient wrt parameters $\gammav$ for expectation-based objectives $\Eb…
stat.ML2017★ 37 cited
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong, Bo Chen, Hongwei Liu +1
It is challenging to develop stochastic gradient based scalable inference for deep discrete latent variable models (LVMs), due to the difficulties in not only computing the gradien…