3 papers
cs.LG2019
Trust-Region Variational Inference with Gaussian Mixture Models
Oleg Arenz, Mingjun Zhong, Gerhard Neumann
Many methods for machine learning rely on approximate inference from intractable probability distributions. Variational inference approximates such distributions by tractable model…
eess.SP2018
Classification of normal/abnormal heart sound recordings based on multi-domain features and back propagation neural network
Hong Tang, Huaming Chen, Ting Li +1
This paper aims to classify a single PCG recording as normal or abnormal for computer-aided diagnosis. The proposed framework for this challenge has four steps: preprocessing, feat…
stat.ML2018
Neural Control Variates for Variance Reduction
Ruosi Wan, Mingjun Zhong, Haoyi Xiong +1
In statistics and machine learning, approximation of an intractable integration is often achieved by using the unbiased Monte Carlo estimator, but the variances of the estimation a…