43 citations · 55 across the 5 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 6 cited
Neural Network Compression Via Sparse Optimization
Tianyi Chen, Bo Ji, Yixin Shi +4
The compression of deep neural networks (DNNs) to reduce inference cost becomes increasingly important to meet realistic deployment requirements of various applications. There have…
math.OC2020★ 2 cited
Half-Space Proximal Stochastic Gradient Method for Group-Sparsity Regularized Problem
Tianyi Chen, Guanyi Wang, Tianyu Ding +3
Optimizing with group sparsity is significant in enhancing model interpretability in machining learning applications, e.g., feature selection, compressed sensing and model compress…
math.OC2020★ 4 cited
Orthant Based Proximal Stochastic Gradient Method for -Regularized Optimization
Tianyi Chen, Tianyu Ding, Bo Ji +6
Sparsity-inducing regularization problems are ubiquitous in machine learning applications, ranging from feature selection to model compression. In this paper, we present a novel st…