11 citations · 17 across the 2 of their papers we have counts for
5 papers
On Kernelized Multi-Armed Bandits with Constraints
Xingyu Zhou, Bo Ji
We study a stochastic bandit problem with a general unknown reward function and a general unknown constraint function. Both functions can be non-linear (even non-convex) and are as…
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…
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…
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…
Generative Adversarial Network for Handwritten Text
Bo Ji, Tianyi Chen
Generative adversarial networks (GANs) have proven hugely successful in variety of applications of image processing. However, generative adversarial networks for handwriting is rel…