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All publications by Tong Zhang
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Adaptive Stochastic Alternating Direction Method of Multipliers
Peilin Zhao, Jinwei Yang, Tong Zhang and Ping Li
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Stochastic Optimization with Importance Sampling for Regularized Loss Minimization
Peilin Zhao and Tong Zhang
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling
Zheng Qu, Peter Richtarik and Tong Zhang
Advances in Neural Information Processing Systems 28, 2015


Local Smoothness in Variance Reduced Optimization
Daniel Vainsencher, Han Liu and Tong Zhang
Advances in Neural Information Processing Systems 28, 2015


Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
Rie Johnson and Tong Zhang
Advances in Neural Information Processing Systems 28, 2015


Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization
Xiaotong Yuan, Ping Li and Tong Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


A Convergence Rate Analysis for LogitBoost, MART and Their Variant
Peng Sun, Tong Zhang and Jie Zhou
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Communication-Efficient Distributed Optimization using an Approximate Newton-type Method
Ohad Shamir, Nati Srebro and Tong Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Shai Shalev-shwartz and Tong Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Accelerated Mini-Batch Stochastic Dual Coordinate Ascent
Shai Shalev-shwartz and Tong Zhang
Advances in Neural Information Processing Systems 26, 2013


Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
Rie Johnson and Tong Zhang
Advances in Neural Information Processing Systems 26, 2013


Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir and Tong Zhang
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Selective Labeling via Error Bound Minimization
Quanquan Gu, Tong Zhang, Jiawei Han and Chris H. Ding
Advances in Neural Information Processing Systems 25, 2012


A Proximal-Gradient Homotopy Method for the L1-Regularized Least-Squares Problem
Lin Xiao and Tong Zhang
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Spectral Methods for Learning Multivariate Latent Tree Structure
Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song and Tong Zhang
Advances in Neural Information Processing Systems 24, 2011


Learning to Search Efficiently in High Dimensions
Zhen Li, Huazhong Ning, Liangliang Cao, Tong Zhang, Yihong Gong and Thomas S. Huang
Advances in Neural Information Processing Systems 24, 2011


Greedy Model Averaging
Dong Dai and Tong Zhang
Advances in Neural Information Processing Systems 24, 2011


Improved Local Coordinate Coding using Local Tangents
Kai Yu and Tong Zhang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


On the Consistency of Feature Selection using Greedy Least Squares Regression
Tong Zhang
Journal of Machine Learning Research, 2009


Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li and Tong Zhang
Journal of Machine Learning Research, 2009


Learning nonlinear dynamic models
John Langford, Ruslan Salakhutdinov and Tong Zhang
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Learning with structured sparsity
Junzhou Huang, Tong Zhang and Dimitris N. Metaxas
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Nonlinear Learning using Local Coordinate Coding
Kai Yu, Tong Zhang and Yihong Gong
Advances in Neural Information Processing Systems 22, 2009


Multi-Label Prediction via Compressed Sensing
John Langford, Tong Zhang, Daniel J. Hsu and Sham M. Kakade
Advances in Neural Information Processing Systems 22, 2009


Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models
Tong Zhang
Advances in Neural Information Processing Systems 21, 2008


Multi-stage Convex Relaxation for Learning with Sparse Regularization
Tong Zhang
Advances in Neural Information Processing Systems 21, 2008


Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li and Tong Zhang
Advances in Neural Information Processing Systems 21, 2008


Two-view feature generation model for semi-supervised learning
Rie K. Ando and Tong Zhang
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information
John Langford and Tong Zhang
Advances in Neural Information Processing Systems 20, 2007


A General Boosting Method and its Application to Learning Ranking Functions for Web Search
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen and Gordon Sun
Advances in Neural Information Processing Systems 20, 2007


On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning
Rie Johnson and Tong Zhang
Journal of Machine Learning Research, 2007


Learning on Graph with Laplacian Regularization
Rie K. Ando and Tong Zhang
Advances in Neural Information Processing Systems 19, 2006


A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
Rie K. Ando and Tong Zhang
Journal of Machine Learning Research, 2005


Solving large scale linear prediction problems using stochastic gradient descent algorithms
Tong Zhang
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Statistical Analysis of Some Multi-Category Large Margin Classification Methods
Tong Zhang
Journal of Machine Learning Research, 2004


Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification
Tong Zhang
Advances in Neural Information Processing Systems 17, 2004


Support Vector Classification with Input Data Uncertainty
Jinbo Bi and Tong Zhang
Advances in Neural Information Processing Systems 17, 2004


On the Convergence of Boosting Procedures
Tong Zhang and Bin Yu
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Learning Bounds for a Generalized Family of Bayesian Posterior Distributions
Tong Zhang
Advances in Neural Information Processing Systems 16, 2003


An Infinity-sample Theory for Multi-category Large Margin Classification
Tong Zhang
Advances in Neural Information Processing Systems 16, 2003


Generalization Error Bounds for Bayesian Mixture Algorithms
Ron Meir and Tong Zhang
Journal of Machine Learning Research, 2003


Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity
Shie Mannor, Ron Meir and Tong Zhang
Journal of Machine Learning Research, 2003


Recommender Systems Using Linear Classifier
Tong Zhang and Vijay S. Iyengar
Journal of Machine Learning Research, 2002


Text Chunking based on a Generalization of Winnow
Tong Zhang, Fred Damerau and David Johnson
Journal of Machine Learning Research, 2002


Covering Number Bounds of Certain Regularized Linear Function Classes
Tong Zhang
Journal of Machine Learning Research, 2002


Effective Dimension and Generalization of Kernel Learning
Tong Zhang
Advances in Neural Information Processing Systems 15, 2002


Data-Dependent Bounds for Bayesian Mixture Methods
Ron Meir and Tong Zhang
Advances in Neural Information Processing Systems 15, 2002