- Learning Bounds for Kernel Regression using Effective Data Dimensionality
- Journal of Machine Learning Research ? (2009) 1-25 Submitted 6/08; 11/08; Published 3/09 Sparse Online Learning via Truncated Gradient
- Active Learning using Adaptive Resampling Vijay S. Iyengar
- Convergence of Large Margin Separable Linear Classification
- Two-view Feature Generation Model for Semi-supervised Learning Rie Kubota Ando rie1@us.ibm.com
- Some Sharp Performance Bounds for Least Squares Regression with L1 Regularization
- A Spectral Algorithm for Learning Hidden Markov Models UC San Diego
- A Discriminative Global Training Algorithm for Statistical MT Christoph Tillmann
- Boosting with Early Stopping: Convergence and Consistency Boosting is one of the most significant advances in machine learning for classification and
- Statistical Analysis of Bayes Optimal Subset David Cossock
- JOURNAL OF AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. X, NO. XX, XXX XXXX 1 An Online Relevant Set Algorithm for Statistical
- Information Theoretical Upper and Lower Bounds for Statistical Estimation
- A Block Bigram Prediction Model for Statistical Machine Translation
- On the Convergence of MDL Density Estimation IBM T.J. Watson Research Center
- Margin Based Active Learning Maria-Florina Balcan1
- Multi-stage Convex Relaxation for Feature Selection Statistics Department
- Sparse Recovery with Orthogonal Matching Pursuit Tong Zhang, Member, IEEE,
- Efficient Optimal Learning for Contextual Bandits Miroslav Dudik
- A Computational Framework for Influenza Antigenic Cartography
- TRADING ACCURACY FOR SPARSITY IN OPTIMIZATION PROBLEMS WITH SPARSITY CONSTRAINTS
- Fundamental Statistical Techniques 1.1 Binary Linear Classification ............................................. 1
- Agnostic Active Learning Without Constraints Anonymous Author(s)
- Improved Local Coordinate Coding using Local Tangents Kai Yu kyu@sv.nec-labs.com
- Journal of Machine Learning Research X (2008) X-X Submitted 5/2008; Published X/XX On the Consistency of Feature Selection using Greedy Least
- Nonlinear Learning using Local Coordinate Coding NEC Laboratories America
- Multi-Label Prediction via Compressed Sensing UC San Diego
- Graph-based Semi-supervised Learning and Spectral Kernel Design
- Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models
- Multi-stage Convex Relaxation for Learning with Sparse Regularization
- Robust Classification of Rare Queries Using Web Knowledge
- From -entropy to KL-entropy: Analysis of Minimum Information Complexity Density Estimation
- Journal of Machine Learning Research X (2005) X-X Submitted 5/2005; Published X/XX A Framework for Learning Predictive Structures from
- A Localized Prediction Model for Statistical Machine Translation Christoph Tillmann and Tong Zhang
- Data Dependent Concentration Bounds for Sequential Prediction Algorithms
- Journal of Machine Learning Research 5 (2004) 12251251 Submitted 4/2004; Published 10/04 Statistical Analysis of Some Multi-Category Large Margin
- Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category
- Focused Named Entity Recognition using Machine IBM China Research
- Column-Generation Boosting Methods for Mixture of Kernels
- Journal of Machine Learning Research 4 (2003) 839-860 Submitted 4/03; Published 10/03 Generalization Error Bounds for Bayesian Mixture Algorithms
- Journal of Machine Learning Research 4 (2003) 713-741 Submitted 11/02; Published 10/03 Greedy Algorithms for Classification Consistency,
- An Infinity-sample Theory for Multi-category Large Margin Classification
- Learning Bounds for a Generalized Family of Bayesian Posterior Distributions
- A decision-tree-based symbolic rule
- A General Greedy Approximation Algorithm with Applications
- Generalization Performance of Some Learning Problems in Hilbert Functional Spaces
- Sparse Online Learning via Truncated Gradient John Langford
- Regularized Winnow Methods Mathematical Sciences Department
- HowtogetaChineseName(Entity): Segmentation and Combination Issues Hongyan Jing Radu Florian Xiaoqiang Luo
- Deep Coding Network Yuanqing Lin
- Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations
- Linear Prediction Models with Graph Regularization for Web-page Categorization
- Support Vector Classification with Input Data Uncertainty
- IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS--II: ANALOG AND DIGITAL SIGNAL PROCESSING, VOL. 47, NO. 4, APRIL 2000 261 A Method for Reduced-Order Modeling and
- Learning with Structured Sparsity Junzhou Huang
- TREC 2005 Genomics Track Experiments at IBM Watson Rie Kubota Ando
- Submitted to the Annals of Statistics THE BENEFIT OF GROUP SPARSITY
- Journal of Machine Learning Research 11 (2010) 1081-1107 Submitted 5/09; Revised 1/10; Published 3/10 Analysis of Multi-stage Convex Relaxation for Sparse Regularization
- Localized Upper and Lower Bounds for Some Estimation Problems
- A Robust Risk Minimization based Named Entity Recognition System IBM T.J. Watson Research Center
- Multi-View Dimensionality Reduction via Canonical Correlation Analysis
- Learning Nonlinear Dynamic Models John Langford jl@yahoo-inc.com
- Robust Matrix Decomposition with Sparse Corruptions
- High Dimensional Nonlinear Learning using Local Coordinate NEC Laboratories America
- Named Entity Recognition through Classifier Combination Radu Florian and Abe Ittycheriah and Hongyan Jing and Tong Zhang
- Updating an NLP System to Fit New Domains: an empirical study on the sentence segmentation problem
- Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation
