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Optimization

14,969 papers

Papers per year

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342
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Papers

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NIPS 2006
Linearly-solvable Markov decision problems NIPS 2006
Fast Computation of Graph Kernels NIPS 2006
Max-margin classification of incomplete data NIPS 2006
No-regret Algorithms for Online Convex Programs NIPS 2006
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NIPS 2006
A Direct Method for Building Sparse Kernel Learning Algorithms JMLR 2006
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines JMLR 2006
Evolutionary Function Approximation for Reinforcement Learning JMLR 2006
Sparse Boosting JMLR 2006
Step Size Adaptation in Reproducing Kernel Hilbert Space JMLR 2006
New Algorithms for Efficient High-Dimensional Nonparametric Classification JMLR 2006
The Interplay of Optimization and Machine Learning Research JMLR 2006
Ensemble Pruning Via Semi-definite Programming JMLR 2006
Linear Programs for Hypotheses Selection in Probabilistic Inference Models JMLR 2006
Bayesian Network Learning with Parameter Constraints JMLR 2006
Maximum-Gain Working Set Selection for SVMs JMLR 2006
Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems JMLR 2006
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006
Large Scale Multiple Kernel Learning JMLR 2006
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra JMLR 2006
Structured Prediction, Dual Extragradient and Bregman Projections JMLR 2006
Considering Cost Asymmetry in Learning Classifiers JMLR 2006
Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006
Streamwise Feature Selection JMLR 2006