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Optimization

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Adaptive Design Optimization in Experiments with People NIPS 2009
An LP View of the M-best MAP problem NIPS 2009
Convex Relaxation of Mixture Regression with Efficient Algorithms NIPS 2009
Periodic Step Size Adaptation for Single Pass On-line Learning NIPS 2009
Adaptive Regularization for Transductive Support Vector Machine NIPS 2009
On the Convergence of the Concave-Convex Procedure NIPS 2009
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis NIPS 2009
Adaptive Regularization of Weight Vectors NIPS 2009
Submodularity Cuts and Applications NIPS 2009
Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing NIPS 2009
Improving Existing Fault Recovery Policies NIPS 2009
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NIPS 2009
Analysis of SVM with Indefinite Kernels NIPS 2009
On Learning Rotations NIPS 2009
A Gaussian Tree Approximation for Integer Least-Squares NIPS 2009
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming NIPS 2009
Ensemble Nystrom Method NIPS 2009
Locality-sensitive binary codes from shift-invariant kernels NIPS 2009
Multiple Incremental Decremental Learning of Support Vector Machines NIPS 2009
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization NIPS 2009
Unsupervised Feature Selection for the $k$-means Clustering Problem NIPS 2009
Efficient and Accurate Lp-Norm Multiple Kernel Learning NIPS 2009
Directed Regression NIPS 2009
Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models NIPS 2009
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NIPS 2009