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Optimization

14207 directly classified papers

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Papers

Progressive mixture rules are deviation suboptimal NIPS 2007
Discriminative Batch Mode Active Learning NIPS 2007
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters JMLR 2007
Infinitely Imbalanced Logistic Regression JMLR 2007
Stagewise Lasso JMLR 2007
Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets" JMLR 2007
Ranking the Best Instances JMLR 2007
Very Fast Online Learning of Highly Non Linear Problems JMLR 2007
Anytime Learning of Decision Trees JMLR 2007
Support Vector Machine Classification with Indefinite Kernels NIPS 2007
Parallelizing Support Vector Machines on Distributed Computers NIPS 2007
Boosting Algorithms for Maximizing the Soft Margin NIPS 2007
Learning with Transformation Invariant Kernels NIPS 2007
A Randomized Algorithm for Large Scale Support Vector Learning NIPS 2007
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting NIPS 2007
Online Linear Regression and Its Application to Model-Based Reinforcement Learning NIPS 2007
Topmoumoute Online Natural Gradient Algorithm NIPS 2007
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs NIPS 2007
CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation NIPS 2007
Cooled and Relaxed Survey Propagation for MRFs NIPS 2007
Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations NIPS 2007
A General Boosting Method and its Application to Learning Ranking Functions for Web Search NIPS 2007
Efficient multiple hyperparameter learning for log-linear models NIPS 2007
Anytime Induction of Cost-sensitive Trees NIPS 2007
Random Sampling of States in Dynamic Programming NIPS 2007