activity
20172019
most citedDensity Functional Estimators with k-Nearest Neighbor Bandwidths

5 citations · 10 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ML20191 cited

Information-Theoretic Understanding of Population Risk Improvement with Model Compression

Yuheng Bu, Weihao Gao, Shaofeng Zou +1

We show that model compression can improve the population risk of a pre-trained model, by studying the tradeoff between the decrease in the generalization error and the increase in…

cs.IT2018

Rate Distortion For Model Compression: From Theory To Practice

Weihao Gao, Yu-Han Liu, Chong Wang +1

The enormous size of modern deep neural networks makes it challenging to deploy those models in memory and communication limited scenarios. Thus, compressing a trained model withou…

cs.LG2018

Learning One-hidden-layer Neural Networks under General Input Distributions

Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh +1

Significant advances have been made recently on training neural networks, where the main challenge is in solving an optimization problem with abundant critical points. However, exi…

stat.ML20174 cited

Discovering Potential Correlations via Hypercontractivity

Hyeji Kim, Weihao Gao, Sreeram Kannan +2

Discovering a correlation from one variable to another variable is of fundamental scientific and practical interest. While existing correlation measures are suitable for discoverin…

cs.IT20175 cited

Density Functional Estimators with k-Nearest Neighbor Bandwidths

Weihao Gao, Sewoong Oh, Pramod Viswanath

Estimating expected polynomials of density functions from samples is a basic problem with numerous applications in statistics and information theory. Although kernel density estima…