COLT 2007

48 papers

A Lower Bound for Agnostically Learning Disjunctions Adam R. Klivans, Alexander A. Sherstov

Aggregation by Exponential Weighting and Sharp Oracle Inequalities Arnak S. Dalalyan, Alexandre B. Tsybakov

An Efficient Re-Scaled Perceptron Algorithm for Conic Systems Alexandre Belloni, Robert M. Freund, Santosh S. Vempala

Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation? Nathan Srebro

Bounded Parameter Markov Decision Processes with Average Reward Criterion Ambuj Tewari, Peter L. Bartlett

Competing with Stationary Prediction Strategies Vladimir Vovk

Gaps in Support Vector Optimization Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart

Generalised Entropy and Asymptotic Complexities of Languages Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin

Generalized SMO-Style Decomposition Algorithms Nikolas List

How Good Is a Kernel When Used as a Similarity Measure? Nathan Srebro

Improved Rates for the Stochastic Continuum-Armed Bandit Problem Peter Auer, Ronald Ortner, Csaba Szepesvári

L1 Regularization in Infinite Dimensional Feature Spaces Saharon Rosset, Grzegorz Swirszcz, Nathan Srebro, Ji Zhu

Learning Correction Grammars Lorenzo Carlucci, John Case, Sanjay Jain

Learning Languages with Rational Kernels Corinna Cortes, Leonid Kontorovich, Mehryar Mohri

Learning Large-Alphabet and Analog Circuits with Value Injection Queries Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin

Learning Nested Halfspaces and Uphill Decision Trees Adam Tauman Kalai

Learning Permutations with Exponential Weights David P. Helmbold, Manfred K. Warmuth

Margin Based Active Learning Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang

Mind Change Optimal Learning of Bayes Net Structure Oliver Schulte, Wei Luo, Russell Greiner

Minimax Bounds for Active Learning Rui M. Castro, Robert D. Nowak

Mitotic Classes Sanjay Jain, Frank Stephan

Multi-View Regression via Canonical Correlation Analysis Sham M. Kakade, Dean P. Foster

Multitask Learning with Expert Advice Jacob D. Abernethy, Peter L. Bartlett, Alexander Rakhlin

Nonlinear Estimators and Tail Bounds for Dimension Reduction in L 1 Using Cauchy Random Projections Ping Li, Trevor Hastie, Kenneth Ward Church

Observational Learning in Random Networks Julian Lorenz, Martin Marciniszyn, Angelika Steger

Occam's Hammer Gilles Blanchard, François Fleuret

On-Line Estimation with the Multivariate Gaussian Distribution Sanjoy Dasgupta, Daniel J. Hsu

Online Learning with Prior Knowledge Elad Hazan, Nimrod Megiddo

Open Problems in Efficient Semi-Supervised PAC Learning Avrim Blum, Maria-Florina Balcan

Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking Sivan Sabato, Shai Shalev-Shwartz

Property Testing: A Learning Theory Perspective Dana Ron

Q -Learning with Linear Function Approximation Francisco S. Melo, M. Isabel Ribeiro

Rademacher Margin Complexity Liwei Wang, Jufu Feng

Regret to the Best vs. Regret to the Average Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman

Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector Sylvain Arlot, Gilles Blanchard, Étienne Roquain

Resource-Bounded Information Gathering for Correlation Clustering Pallika H. Kanani, Andrew McCallum

Robust Reductions from Ranking to Classification Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin

Sketching Information Divergences Sudipto Guha, Piotr Indyk, Andrew McGregor

Sparse Density Estimation with L1 Penalties Florentina Bunea, Alexandre B. Tsybakov, Marten H. Wegkamp

Spectral Algorithms for Learning and Clustering Santosh S. Vempala

Stability of K -Means Clustering Shai Ben-David, Dávid Pál, Hans Ulrich Simon

Strategies for Prediction Under Imperfect Monitoring Gábor Lugosi, Shie Mannor, Gilles Stoltz

Suboptimality of Penalized Empirical Risk Minimization in Classification Guillaume Lecué

Teaching Dimension and the Complexity of Active Learning Steve Hanneke

The Loss Rank Principle for Model Selection Marcus Hutter

Transductive Rademacher Complexity and Its Applications Ran El-Yaniv, Dmitry Pechyony

U-Shaped, Iterative, and Iterative-with-Counter Learning John Case, Samuel E. Moelius

When Is There a Free Matrix Lunch? Manfred K. Warmuth