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Optimization

14,983 papers

Papers per year

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Papers

Learning Monotonic Transformations for Classification NIPS 2007
Online Linear Regression and Its Application to Model-Based Reinforcement Learning NIPS 2007
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting NIPS 2007
A Randomized Algorithm for Large Scale Support Vector Learning NIPS 2007
Support Vector Machine Classification with Indefinite Kernels NIPS 2007
Learning with Transformation Invariant Kernels NIPS 2007
Efficient Convex Relaxation for Transductive Support Vector Machine NIPS 2007
Message Passing for Max-weight Independent Set NIPS 2007
Boosting the Area under the ROC Curve NIPS 2007
A Risk Minimization Principle for a Class of Parzen Estimators NIPS 2007
Discriminative Batch Mode Active Learning NIPS 2007
What makes some POMDP problems easy to approximate? NIPS 2007
Boosting Algorithms for Maximizing the Soft Margin NIPS 2007
Parallelizing Support Vector Machines on Distributed Computers NIPS 2007
Selecting Observations against Adversarial Objectives NIPS 2007
Progressive mixture rules are deviation suboptimal NIPS 2007
Hierarchical Penalization NIPS 2007
Linear programming analysis of loopy belief propagation for weighted matching NIPS 2007
Consistent Minimization of Clustering Objective Functions NIPS 2007
Minimax Regret Classifier for Imprecise Class Distributions JMLR 2007
Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets" JMLR 2007
A Stochastic Algorithm for Feature Selection in Pattern Recognition JMLR 2007
Infinitely Imbalanced Logistic Regression JMLR 2007
Concave Learners for Rankboost JMLR 2007
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters JMLR 2007