Universal Multi-Task Kernels.
An Information Criterion for Variable Selection in Support Vector Machines.
Classification with a Reject Option using a Hinge Loss.
Algorithms for Sparse Linear Classifiers in the Massive Data Setting.
Aggregation of SVM Classifiers Using Sobolev Spaces.
Manifold Learning: The Price of Normalization.
On the Suitable Domain for SVM Training in Image Coding.
Value Function Based Reinforcement Learning in Changing Markovian Environments.
Consistency of the Group Lasso and Multiple Kernel Learning.
A Library for Locally Weighted Projection Regression.
Generalization from Observed to Unobserved Features by Clustering.
Search for Additive Nonlinear Time Series Causal Models.
Complete Identification Methods for the Causal Hierarchy.
Trust Region Newton Method for Logistic Regression.
Closed Sets for Labeled Data.
Learning Control Knowledge for Forward Search Planning.
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction.
Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns.
Ranking Categorical Features Using Generalization Properties.
Online Learning of Complex Prediction Problems Using Simultaneous Projections.
Discriminative Learning of Max-Sum Classifiers.
A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters.
Learning from Multiple Sources.
Learning Similarity with Operator-valued Large-margin Classifiers.
On Relevant Dimensions in Kernel Feature Spaces.
Nearly Uniform Validation Improves Compression-Based Error Bounds.
Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods.
A Recursive Method for Structural Learning of Directed Acyclic Graphs.
Mixed Membership Stochastic Blockmodels.
Optimization Techniques for Semi-Supervised Support Vector Machines.
Max-margin Classification of Data with Absent Features.
Regularization on Graphs with Function-adapted Diffusion Processes.
Support Vector Machinery for Infinite Ensemble Learning.
Learning to Combine Motor Primitives Via Greedy Additive Regression.
Shark.
An Error Bound Based on a Worst Likely Assignment.
Hit Miss Networks with Applications to Instance Selection.
Optimal Solutions for Sparse Principal Component Analysis.
Consistency of Trace Norm Minimization.
Using Markov Blankets for Causal Structure Learning.
Finite-Time Bounds for Fitted Value Iteration.
Maximal Causes for Non-linear Component Extraction.
Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data.
Comments on the Complete Characterization of a Family of Solutions to a Generalized
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models.
Active Learning by Spherical Subdivision.
A Tutorial on Conformal Prediction.
Learning Balls of Strings from Edit Corrections.
Bayesian Inference and Optimal Design for the Sparse Linear Model.
Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming.
Linear-Time Computation of Similarity Measures for Sequential Data.
LIBLINEAR: A Library for Large Linear Classification.
Multi-class Discriminant Kernel Learning via Convex Programming.
Evidence Contrary to the Statistical View of Boosting.
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks.
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines.
Bouligand Derivatives and Robustness of Support Vector Machines for Regression.
Causal Reasoning with Ancestral Graphs.
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers.
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2.
A New Algorithm for Estimating the Effective Dimension-Reduction Subspace.
Consistency of Random Forests and Other Averaging Classifiers.
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies.
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective.
A Bahadur Representation of the Linear Support Vector Machine.
Accelerated Neural Evolution through Cooperatively Coevolved Synapses.
