156 citations · 391 across the 43 of their papers we have counts for
4 papers · 1 filter
Adaptive Hierarchical Hyper-gradient Descent
Renlong Jie, Junbin Gao, Andrey Vasnev +1
In this study, we investigate learning rate adaption at different levels based on the hyper-gradient descent framework and propose a method that adaptively learns the optimizer par…
Variational Bayes on Manifolds
Minh-Ngoc Tran, Dang H. Nguyen, Duy Nguyen
Variational Bayes (VB) has become a widely-used tool for Bayesian inference in statistics and machine learning. Nonetheless, the development of the existing VB algorithms is so far…
Manifold Optimization Assisted Gaussian Variational Approximation
Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran +1
Gaussian variational approximation is a popular methodology to approximate posterior distributions in Bayesian inference especially in high dimensional and large data settings. To…
Model Selection with the Loss Rank Principle
Marcus Hutter, Minh-Ngoc Tran
A key issue in statistics and machine learning is to automatically select the "right" model complexity, e.g., the number of neighbors to be averaged over in k nearest neighbor (kNN…