411 citations · 3k across the 39 of their papers we have counts for
6 papers · 1 filter
Some sharp performance bounds for least squares regression with regularization
Tong Zhang
We derive sharp performance bounds for least squares regression with regularization from parameter estimation accuracy and feature selection quality perspectives. The main re…
High Dimensional Nonlinear Learning using Local Coordinate Coding
Kai Yu, Tong Zhang
This paper introduces a new method for semi-supervised learning on high dimensional nonlinear manifolds, which includes a phase of unsupervised basis learning and a phase of superv…
Learning Nonlinear Dynamic Models
John Langford, Ruslan Salakhutdinov, Tong Zhang
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sho…
Learning with Structured Sparsity
Junzhou Huang, Tong Zhang, Dimitris Metaxas
This paper investigates a new learning formulation called structured sparsity, which is a natural extension of the standard sparsity concept in statistical learning and compressive…
Multi-Label Prediction via Compressed Sensing
Daniel Hsu, Sham M. Kakade, John Langford +1
We consider multi-label prediction problems with large output spaces under the assumption of output sparsity -- that the target (label) vectors have small support. We develop a gen…
The Benefit of Group Sparsity
Junzhou Huang, Tong Zhang
This paper develops a theory for group Lasso using a concept called strong group sparsity. Our result shows that group Lasso is superior to standard Lasso for strongly group-sparse…