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Optimization

14207 directly classified papers

Papers per year

Papers

Reproducing Kernel Banach Spaces for Machine Learning JMLR 2009
The P-Norm Push: A Simple Convex Ranking Algorithm that Concentrates at the Top of the List JMLR 2009
Matrix Completion from Noisy Entries NIPS 2009
Fast Prediction on a Tree NIPS 2008
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform NIPS 2008
Accelerated Neural Evolution through Cooperatively Coevolved Synapses JMLR 2008
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks JMLR 2008
Gradient Tree Boosting for Training Conditional Random Fields JMLR 2008
SimpleMKL JMLR 2008
Proofs and Experiments in Scalable, Near-Optimal Search by Multiple Robots RSS 2008
Adapting to a Market Shock: Optimal Sequential Market-Making NIPS 2008
Tighter Bounds for Structured Estimation NIPS 2008
Exact Convex Confidence-Weighted Learning NIPS 2008
PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning NIPS 2008
Differentiable Sparse Coding NIPS 2008
Inferring rankings under constrained sensing NIPS 2008
Nonparametric regression and classification with joint sparsity constraints NIPS 2008
A Convex Upper Bound on the Log-Partition Function for Binary Distributions NIPS 2008
Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models NIPS 2008
Efficient Exact Inference in Planar Ising Models NIPS 2008
Sparsity of SVMs that use the epsilon-insensitive loss NIPS 2008
Clustered Multi-Task Learning: A Convex Formulation NIPS 2008
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning NIPS 2008
Multi-label Multiple Kernel Learning NIPS 2008
A general framework for investigating how far the decoding process in the brain can be simplified NIPS 2008