4 papers · 1 filter
Generative Particle Variational Inference via Estimation of Functional Gradients
Neale Ratzlaff, Qinxun Bai, Li Fuxin +1
Recently, particle-based variational inference (ParVI) methods have gained interest because they can avoid arbitrary parametric assumptions that are common in variational inference…
Implicit Generative Modeling for Efficient Exploration
Neale Ratzlaff, Qinxun Bai, Li Fuxin +1
Efficient exploration remains a challenging problem in reinforcement learning, especially for those tasks where rewards from environments are sparse. A commonly used approach for e…
A Topological Regularizer for Classifiers via Persistent Homology
Chao Chen, Xiuyan Ni, Qinxun Bai +1
Regularization plays a crucial role in supervised learning. Most existing methods enforce a global regularization in a structure agnostic manner. In this paper, we initiate a new d…
A Bayesian Approach for Online Classifier Ensemble
Qinxun Bai, Henry Lam, Stan Sclaroff
We propose a Bayesian approach for recursively estimating the classifier weights in online learning of a classifier ensemble. In contrast with past methods, such as stochastic grad…