Tong Zhang

According to our database1, Tong Zhang authored at least 212 papers between 1996 and 2020.

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Bibliography

2020
Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold.
SIAM J. Optim., 2020

End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Accelerated dual-averaging primal-dual method for composite convex minimization.
Optimization Methods and Software, 2020

MAP Inference Via ℓ <sub>2</sub>-Sphere Linear Program Reformulation.
Int. J. Comput. Vis., 2020

Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization.
CoRR, 2020

Multi-consensus Decentralized Accelerated Gradient Descent.
CoRR, 2020

MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation.
CoRR, 2020

Mean-Field Analysis of Two-Layer Neural Networks: Non-Asymptotic Rates and Generalization Bounds.
CoRR, 2020

Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems.
CoRR, 2020

Black-Box Adversarial Attack with Transferable Model-based Embedding.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models.
J. Mach. Learn. Res., 2019

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
J. Mach. Learn. Res., 2019

Fast Generalized Matrix Regression with Applications in Machine Learning.
CoRR, 2019

Convex Formulation of Overparameterized Deep Neural Networks.
CoRR, 2019

Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations.
CoRR, 2019

Mirror Natural Evolution Strategies.
CoRR, 2019

MAP Inference via L2-Sphere Linear Program Reformulation.
CoRR, 2019

Efficient Decision-based Black-box Adversarial Attacks on Face Recognition.
CoRR, 2019

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.
CoRR, 2019

Graph-guided multi-task sparse learning model: a method for identifying antigenic variants of influenza A(H3N2) virus.
Bioinform., 2019

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.
IEEE Access, 2019

Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Sharp Analysis for Nonconvex SGD Escaping from Saddle Points.
Proceedings of the Conference on Learning Theory, 2019

Sentiment Analysis Using Autoregressive Language Modeling and Broad Learning System.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
Bayesian Model Averaging With Exponentiated Least Squares Loss.
IEEE Trans. Inf. Theory, 2018

Learning to Remember Translation History with a Continuous Cache.
Trans. Assoc. Comput. Linguistics, 2018

Near-optimal stochastic approximation for online principal component estimation.
Math. Program., 2018

Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack.
CoRR, 2018

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning.
CoRR, 2018

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space.
CoRR, 2018

Fully Implicit Online Learning.
CoRR, 2018

TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game.
CoRR, 2018

A convex formulation for high-dimensional sparse sliced inverse regression.
CoRR, 2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
CoRR, 2018

Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Gradient Sparsification for Communication-Efficient Distributed Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Exponentially Weighted Imitation Learning for Batched Historical Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adaptive Sampling Towards Fast Graph Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents.
Proceedings of the 35th International Conference on Machine Learning, 2018

Safe Element Screening for Submodular Function Minimization.
Proceedings of the 35th International Conference on Machine Learning, 2018

Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization.
Proceedings of the 35th International Conference on Machine Learning, 2018

Graphical Nonconvex Optimization via an Adaptive Convex Relaxation.
Proceedings of the 35th International Conference on Machine Learning, 2018

An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method.
Proceedings of the 35th International Conference on Machine Learning, 2018

End-to-end Active Object Tracking via Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Composite Functional Gradient Learning of Generative Adversarial Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Super-Identity Convolutional Neural Network for Face Hallucination.
Proceedings of the Computer Vision - ECCV 2018, 2018

Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition.
Proceedings of the Computer Vision - ECCV 2018, 2018

Modeling Varying Camera-IMU Time Offset in Optimization-Based Visual-Inertial Odometry.
Proceedings of the Computer Vision - ECCV 2018, 2018

Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks.
Proceedings of the Computer Vision - ECCV 2018, 2018

Recurrent Fusion Network for Image Captioning.
Proceedings of the Computer Vision - ECCV 2018, 2018

Neural Stereoscopic Image Style Transfer.
Proceedings of the Computer Vision - ECCV 2018, 2018

Video Re-localization.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Sparseness Analysis in the Pretraining of Deep Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., 2017

Candidates v.s. Noises Estimation for Large Multi-Class Classification Problem.
CoRR, 2017

Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations.
CoRR, 2017

On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions.
CoRR, 2017

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Distributed Learning with Sparsity.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Pyramid Convolutional Neural Networks for Text Categorization.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization.
Math. Program., 2016

Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level.
CoRR, 2016

Supervised and Semi-Supervised Text Categorization using One-Hot LSTM for Region Embeddings.
CoRR, 2016

Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression.
CoRR, 2016

Learning Additive Exponential Family Graphical Models via \ell_{2, 1}-norm Regularized M-Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Exact Recovery of Hard Thresholding Pursuit.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Fundamentals of Predictive Text Mining, Second Edition
Texts in Computer Science, Springer, ISBN: 978-1-4471-6750-1, 2015

Learning sparse low-threshold linear classifiers.
J. Mach. Learn. Res., 2015

Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference.
CoRR, 2015

Semi-Supervised Learning with Multi-View Embedding: Theory and Application with Convolutional Neural Networks.
CoRR, 2015

Local Smoothness in Variance Reduced Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Effective Use of Word Order for Text Categorization with Convolutional Neural Networks.
Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

2014
Partial Gaussian Graphical Model Estimation.
IEEE Trans. Inf. Theory, 2014

A Proximal Stochastic Gradient Method with Progressive Variance Reduction.
SIAM J. Optim., 2014

Learning Nonlinear Functions Using Regularized Greedy Forest.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory.
CoRR, 2014

Randomized Dual Coordinate Ascent with Arbitrary Sampling.
CoRR, 2014

Sparse Recovery with Very Sparse Compressed Counting.
CoRR, 2014

Batch-Mode Active Learning via Error Bound Minimization.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization.
Proceedings of the 31th International Conference on Machine Learning, 2014

Communication-Efficient Distributed Optimization using an Approximate Newton-type Method.
Proceedings of the 31th International Conference on Machine Learning, 2014

Compressed Counting Meets Compressed Sensing.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem.
SIAM J. Optim., 2013

Truncated power method for sparse eigenvalue problems.
J. Mach. Learn. Res., 2013

Stochastic dual coordinate ascent methods for regularized loss.
J. Mach. Learn. Res., 2013

Aggregation of Affine Estimators.
CoRR, 2013

High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Accelerated Mini-Batch Stochastic Dual Coordinate Ascent.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Accelerating Stochastic Gradient Descent using Predictive Variance Reduction.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Random Design Analysis of Ridge Regression.
Proceedings of the COLT 2012, 2012

A spectral algorithm for learning Hidden Markov Models.
J. Comput. Syst. Sci., 2012

Analysis of a randomized approximation scheme for matrix multiplication
CoRR, 2012

Proximal Stochastic Dual Coordinate Ascent
CoRR, 2012

Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
CoRR, 2012

Deviation Optimal Learning using Greedy Q-aggregation
CoRR, 2012

AntigenMap 3D: an online antigenic cartography resource.
Bioinform., 2012

Selective Labeling via Error Bound Minimization.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Proximal-Gradient Homotopy Method for the L1-Regularized Least-Squares Problem.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Sparse Recovery With Orthogonal Matching Pursuit Under RIP.
IEEE Trans. Inf. Theory, 2011

Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations.
IEEE Trans. Inf. Theory, 2011

Robust Matrix Decomposition With Sparse Corruptions.
IEEE Trans. Inf. Theory, 2011

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation.
PLoS Comput. Biol., 2011

Learning with Structured Sparsity.
J. Mach. Learn. Res., 2011

A tail inequality for quadratic forms of subgaussian random vectors
CoRR, 2011

An Analysis of Random Design Linear Regression
CoRR, 2011

Dimension-free tail inequalities for sums of random matrices.
CoRR, 2011

Efficient Optimal Learning for Contextual Bandits.
Proceedings of the UAI 2011, 2011

Learning to Search Efficiently in High Dimensions.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Greedy Model Averaging.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Spectral Methods for Learning Multivariate Latent Tree Structure.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Fundamentals of Predictive Text Mining.
Texts in Computer Science 41, Springer, ISBN: 978-1-84996-226-1, 2010

Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints.
SIAM J. Optim., 2010

A Computational Framework for Influenza Antigenic Cartography.
PLoS Comput. Biol., 2010

Analysis of Multi-stage Convex Relaxation for Sparse Regularization.
J. Mach. Learn. Res., 2010

Robust Matrix Decomposition with Outliers
CoRR, 2010

Deep Coding Network.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Agnostic Active Learning Without Constraints.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Improved Local Coordinate Coding using Local Tangents.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Image Classification Using Super-Vector Coding of Local Image Descriptors.
Proceedings of the Computer Vision - ECCV 2010, 2010

2009
Classifying search queries using the Web as a source of knowledge.
ACM Trans. Web, 2009

On the Consistency of Feature Selection using Greedy Least Squares Regression.
J. Mach. Learn. Res., 2009

Sparse Online Learning via Truncated Gradient.
J. Mach. Learn. Res., 2009

Nonlinear Learning using Local Coordinate Coding.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Multi-Label Prediction via Compressed Sensing.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Learning nonlinear dynamic models.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Graph-Based Semi-Supervised Learning and Spectral Kernel Design.
IEEE Trans. Inf. Theory, 2008

Statistical Analysis of Bayes Optimal Subset Ranking.
IEEE Trans. Inf. Theory, 2008

An Online Relevant Set Algorithm for Statistical Machine Translation.
IEEE Trans. Speech Audio Process., 2008

Multi-stage Convex Relaxation for Learning with Sparse Regularization.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
A block bigram prediction model for statistical machine translation.
ACM Trans. Speech Lang. Process., 2007

On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning.
J. Mach. Learn. Res., 2007

Robust classification of rare queries using web knowledge.
Proceedings of the SIGIR 2007: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2007

A General Boosting Method and its Application to Learning Ranking Functions for Web Search.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Two-view feature generation model for semi-supervised learning.
Proceedings of the Machine Learning, 2007

Margin Based Active Learning.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Information-theoretic upper and lower bounds for statistical estimation.
IEEE Trans. Inf. Theory, 2006

Learning on Graph with Laplacian Regularization.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Linear prediction models with graph regularization for web-page categorization.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Subset Ranking Using Regression.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

Effectiveness of Meeting Outcomes in Virtual vs. Face-to-Face Teams: A Comparison Study in China.
Proceedings of the Connecting the Americas. 12th Americas Conference on Information Systems, 2006

A Discriminative Global Training Algorithm for Statistical MT.
Proceedings of the ACL 2006, 2006

2005
Learning Bounds for Kernel Regression Using Effective Data Dimensionality.
Neural Comput., 2005

A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data.
J. Mach. Learn. Res., 2005

TREC 2005 Genomics Track Experiments at IBM Watson.
Proceedings of the Fourteenth Text REtrieval Conference, 2005

Analysis of Spectral Kernel Design based Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Localized Upper and Lower Bounds for Some Estimation Problems.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

Data Dependent Concentration Bounds for Sequential Prediction Algorithms.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

A Localized Prediction Model for Statistical Machine Translation.
Proceedings of the ACL 2005, 2005

A High-Performance Semi-Supervised Learning Method for Text Chunking.
Proceedings of the ACL 2005, 2005

2004
Statistical Analysis of Some Multi-Category Large Margin Classification Methods.
J. Mach. Learn. Res., 2004

Text categorization for a comprehensive time-dependent benchmark.
Inf. Process. Manag., 2004

Focused named entity recognition using machine learning.
Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Support Vector Classification with Input Data Uncertainty.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Column-generation boosting methods for mixture of kernels.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Chinese Named Entity Recognition Based on Multilevel Linguistic Features.
Proceedings of the Natural Language Processing, 2004

Solving large scale linear prediction problems using stochastic gradient descent algorithms.
Proceedings of the Machine Learning, 2004

On the Convergence of MDL Density Estimation.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
Sequential greedy approximation for certain convex optimization problems.
IEEE Trans. Inf. Theory, 2003

Leave-One-Out Bounds for Kernel Methods.
Neural Comput., 2003

Generalization Error Bounds for Bayesian Mixture Algorithms.
J. Mach. Learn. Res., 2003

Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity.
J. Mach. Learn. Res., 2003

Learning Bounds for a Generalized Family of Bayesian Posterior Distributions.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

An Infinity-sample Theory for Multi-category Large Margin Classification.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

On the Convergence of Boosting Procedures.
Proceedings of the Machine Learning, 2003

HowtogetaChineseName(Entity): Segmentation and Combination Issues.
Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2003

Named Entity Recognition through Classifier Combination.
Proceedings of the Seventh Conference on Natural Language Learning, 2003

A Robust Risk Minimization based Named Entity Recognition System.
Proceedings of the Seventh Conference on Natural Language Learning, 2003

Updating an NLP system to fit new domains: an empirical study on the sentence segmentation problem.
Proceedings of the Seventh Conference on Natural Language Learning, 2003

2002
Two-Sided Arnoldi and Nonsymmetric Lanczos Algorithms.
SIAM J. Matrix Anal. Appl., 2002

Approximation Bounds for Some Sparse Kernel Regression Algorithms.
Neural Comput., 2002

On the Dual Formulation of Regularized Linear Systems with Convex Risks.
Mach. Learn., 2002

Recommender Systems Using Linear Classifier.
J. Mach. Learn. Res., 2002

Text Chunking based on a Generalization of Winnow.
J. Mach. Learn. Res., 2002

Covering Number Bounds of Certain Regularized Linear Function Classes.
J. Mach. Learn. Res., 2002

On the Consistency of Instantaneous Rigid Motion Estimation.
Int. J. Comput. Vis., 2002

A decision-tree-based symbolic rule induction system for text categorization.
IBM Syst. J., 2002

Experiments in high-dimensional text categorization.
Proceedings of the SIGIR 2002: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2002

Effective Dimension and Generalization of Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Data-Dependent Bounds for Bayesian Mixture Methods.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Statistical Behavior and Consistency of Support Vector Machines, Boosting, and Beyond.
Proceedings of the Machine Learning, 2002

The Consistency of Greedy Algorithms for Classification.
Proceedings of the Computational Learning Theory, 2002

2001
Rank-One Approximation to High Order Tensors.
SIAM J. Matrix Anal. Appl., 2001

Text Categorization Based on Regularized Linear Classification Methods.
Inf. Retr., 2001

An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods.
AI Mag., 2001

Empirical Study of Recommender Systems Using Linear Classifiers.
Proceedings of the Knowledge Discovery and Data Mining, 2001

Some Sparse Approximation Bounds for Regression Problems.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

A Leave-One-out Cross Validation Bound for Kernel Methods with Applications in Learning.
Proceedings of the Computational Learning Theory, 2001

A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning.
Proceedings of the Computational Learning Theory, 2001

Text Chunking using Regularized Winnow.
Proceedings of the Association for Computational Linguistic, 2001

2000
Regularized Winnow Methods.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Convergence of Large Margin Separable Linear Classification.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Active learning using adaptive resampling.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1999
Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Fast, Robust, and Consistent Camera Motion Estimation.
Proceedings of the 1999 Conference on Computer Vision and Pattern Recognition (CVPR '99), 1999

Theoretical Analysis of a Class of Randomized Regularization Methods.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
On the Homotopy Method for Perturbed Symmetric Generalized Eigenvalue Problems.
SIAM J. Sci. Comput., 1998

A Linear Algorithm for Optimal Context Clustering with Application to Bi-level Image Coding.
Proceedings of the 1998 IEEE International Conference on Image Processing, 1998

Compression by Model Combination.
Proceedings of the Data Compression Conference, 1998

1996
Optimal Surface Smoothing as Filter Design.
Proceedings of the Computer Vision, 1996


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