List of works - Tong Zhang

Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding

scientific article published on December 1, 2015

Convergence of Large Margin Separable Linear Classification

Analysis of Spectral Kernel Design based Semi-supervised Learning

scientific article published in January 2006

Deep Subspace Clustering Networks

scientific article published in January 2017

Learning Additive Exponential Family Graphical Models via

scientific article published in January 2016

Divergence-Augmented Policy Optimization

Nonlinear Learning using Local Coordinate Coding

Hashtag-Guided Low-Resource Tweet Classification

scientific article published on 26 April 2023

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator

scientific article

Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity

Local Smoothness in Variance Reduced Optimization

Learning on Graph with Laplacian Regularization

scientific article published in January 2007

Deep Coding Network

Learning Bounds for a Generalized Family of Bayesian Posterior Distributions

scientific article published in January 2004

Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models

Effective Dimension and Generalization of Kernel Learning

scientific article published in January 2003

An Infinity-sample Theory for Multi-category Large Margin Classification

scientific article published in January 2004

Greedy Model Averaging

scientific article published in January 2011

Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification

Exact Recovery of Hard Thresholding Pursuit

scientific article published in January 2016

Exponentially Weighted Imitation Learning for Batched Historical Data

Accelerating Stochastic Gradient Descent using Predictive Variance Reduction

Accelerated Mini-Batch Stochastic Dual Coordinate Ascent

Support Vector Classification with Input Data Uncertainty

scientific article published in January 2005

Regularized Winnow Methods

Learning to Search Efficiently in High Dimensions

scientific article published in January 2011

Selective Labeling via Error Bound Minimization

scientific article published in January 2012

Gradient Sparsification for Communication-Efficient Distributed Optimization

article by Jianqiao Wangni et al published 2018 in Advances in Neural Information Processing Systems 31

Spectral Methods for Learning Multivariate Latent Tree Structure

scientific article published in January 2011

Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding

article

Diffusion Approximations for Online Principal Component Estimation and Global Convergence

scientific article published in January 2017

Stochastic Expectation Maximization with Variance Reduction

The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information

scientific article published in January 2008

Sparse Online Learning via Truncated Gradient

Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning

scientific article published in January 2017

Data-Dependent Bounds for Bayesian Mixture Methods

scientific article published in January 2003

Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling

Multi-stage Convex Relaxation for Learning with Sparse Regularization

Multi-Label Prediction via Compressed Sensing

scientific article published in January 2009

Adaptive Sampling Towards Fast Graph Representation Learning

Communication Compression for Decentralized Training

article by Hanlin Tang et al published 2018 in Advances in Neural Information Processing Systems 31

A General Boosting Method and its Application to Learning Ranking Functions for Web Search

scientific article published in January 2008

List of works by Tong Zhang

Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding

Convergence of Large Margin Separable Linear Classification

Analysis of Spectral Kernel Design based Semi-supervised Learning

Deep Subspace Clustering Networks

Learning Additive Exponential Family Graphical Models via

Divergence-Augmented Policy Optimization

Nonlinear Learning using Local Coordinate Coding

Hashtag-Guided Low-Resource Tweet Classification

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator

Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity

Local Smoothness in Variance Reduced Optimization

Learning on Graph with Laplacian Regularization

Deep Coding Network

Learning Bounds for a Generalized Family of Bayesian Posterior Distributions

Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models

Effective Dimension and Generalization of Kernel Learning

An Infinity-sample Theory for Multi-category Large Margin Classification

Greedy Model Averaging

Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification

Exact Recovery of Hard Thresholding Pursuit

Exponentially Weighted Imitation Learning for Batched Historical Data

Accelerating Stochastic Gradient Descent using Predictive Variance Reduction

Accelerated Mini-Batch Stochastic Dual Coordinate Ascent

Support Vector Classification with Input Data Uncertainty

Regularized Winnow Methods

Learning to Search Efficiently in High Dimensions

Selective Labeling via Error Bound Minimization

Gradient Sparsification for Communication-Efficient Distributed Optimization

Spectral Methods for Learning Multivariate Latent Tree Structure

Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding

Diffusion Approximations for Online Principal Component Estimation and Global Convergence

Stochastic Expectation Maximization with Variance Reduction

The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information

Sparse Online Learning via Truncated Gradient

Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning

Data-Dependent Bounds for Bayesian Mixture Methods

Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling

Multi-stage Convex Relaxation for Learning with Sparse Regularization

Multi-Label Prediction via Compressed Sensing

Adaptive Sampling Towards Fast Graph Representation Learning

Communication Compression for Decentralized Training

A General Boosting Method and its Application to Learning Ranking Functions for Web Search

Agnostic Active Learning Without Constraints