COLT A*

47 papers

YearTitle / Authors
2007A Lower Bound for Agnostically Learning Disjunctions.
Adam R. Klivans, Alexander A. Sherstov
2007Aggregation by Exponential Weighting and Sharp Oracle Inequalities.
Arnak S. Dalalyan, Alexandre B. Tsybakov
2007An Efficient Re-scaled Perceptron Algorithm for Conic Systems.
Alexandre Belloni, Robert M. Freund, Santosh S. Vempala
2007Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation?
Nathan Srebro
2007Bounded Parameter Markov Decision Processes with Average Reward Criterion.
Ambuj Tewari, Peter L. Bartlett
2007Competing with Stationary Prediction Strategies.
Vladimir Vovk
2007Gaps in Support Vector Optimization.
Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart
2007Generalised Entropy and Asymptotic Complexities of Languages.
Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin
2007Generalized SMO-Style Decomposition Algorithms.
Nikolas List
2007How Good Is a Kernel When Used as a Similarity Measure?
Nathan Srebro
2007Improved Rates for the Stochastic Continuum-Armed Bandit Problem.
Peter Auer, Ronald Ortner, Csaba Szepesvári
2007Learning Correction Grammars.
Lorenzo Carlucci, John Case, Sanjay Jain
2007Learning Languages with Rational Kernels.
Corinna Cortes, Leonid Kontorovich, Mehryar Mohri
2007Learning Large-Alphabet and Analog Circuits with Value Injection Queries.
Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin
2007Learning Nested Halfspaces and Uphill Decision Trees.
Adam Tauman Kalai
2007Learning Permutations with Exponential Weights.
David P. Helmbold, Manfred K. Warmuth
2007Learning Theory, 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007, Proceedings
Nader H. Bshouty, Claudio Gentile
2007Margin Based Active Learning.
Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang
2007Mind Change Optimal Learning of Bayes Net Structure.
Oliver Schulte, Wei Luo, Russell Greiner
2007Minimax Bounds for Active Learning.
Rui M. Castro, Robert D. Nowak
2007Mitotic Classes.
Sanjay Jain, Frank Stephan
2007Multi-view Regression Via Canonical Correlation Analysis.
Sham M. Kakade, Dean P. Foster
2007Multitask Learning with Expert Advice.
Jacob D. Abernethy, Peter L. Bartlett, Alexander Rakhlin
2007Nonlinear Estimators and Tail Bounds for Dimension Reduction in
Ping Li, Trevor Hastie, Kenneth Ward Church
2007Observational Learning in Random Networks.
Julian Lorenz, Martin Marciniszyn, Angelika Steger
2007Occam's Hammer.
Gilles Blanchard, François Fleuret
2007On-Line Estimation with the Multivariate Gaussian Distribution.
Sanjoy Dasgupta, Daniel J. Hsu
2007Online Learning with Prior Knowledge.
Elad Hazan, Nimrod Megiddo
2007Open Problems in Efficient Semi-supervised PAC Learning.
Avrim Blum, Maria-Florina Balcan
2007Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking.
Sivan Sabato, Shai Shalev-Shwartz
2007Property Testing: A Learning Theory Perspective.
Dana Ron
2007Rademacher Margin Complexity.
Liwei Wang, Jufu Feng
2007Regret to the Best vs. Regret to the Average.
Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman
2007Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector.
Sylvain Arlot, Gilles Blanchard, Étienne Roquain
2007Resource-Bounded Information Gathering for Correlation Clustering.
Pallika H. Kanani, Andrew McCallum
2007Robust Reductions from Ranking to Classification.
Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin
2007Sketching Information Divergences.
Sudipto Guha, Piotr Indyk, Andrew McGregor
2007Sparse Density Estimation with
Florentina Bunea, Alexandre B. Tsybakov, Marten H. Wegkamp
2007Spectral Algorithms for Learning and Clustering.
Santosh S. Vempala
2007Stability of
Shai Ben-David, Dávid Pál, Hans Ulrich Simon
2007Strategies for Prediction Under Imperfect Monitoring.
Gábor Lugosi, Shie Mannor, Gilles Stoltz
2007Suboptimality of Penalized Empirical Risk Minimization in Classification.
Guillaume Lecué
2007Teaching Dimension and the Complexity of Active Learning.
Steve Hanneke
2007The Loss Rank Principle for Model Selection.
Marcus Hutter
2007Transductive Rademacher Complexity and Its Applications.
Ran El-Yaniv, Dmitry Pechyony
2007U-Shaped, Iterative, and Iterative-with-Counter Learning.
John Case, Samuel E. Moelius
2007When Is There a Free Matrix Lunch?
Manfred K. Warmuth