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Optimization

14207 directly classified papers

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Papers

Multiclass Boosting: Theory and Algorithms NIPS 2011
Sparse Recovery with Brownian Sensing NIPS 2011
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NIPS 2011
Large-Scale Sparse Principal Component Analysis with Application to Text Data NIPS 2011
Regret Bounds for the Adaptive Control of Linear Quadratic Systems COLT 2011
Blackwell Approachability and No-Regret Learning are Equivalent COLT 2011
Competitive Closeness Testing COLT 2011
Metric Learning with Multiple Kernels NIPS 2011
Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts NIPS 2011
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation NIPS 2011
Nearest Neighbor based Greedy Coordinate Descent NIPS 2011
Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons NIPS 2011
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements NIPS 2011
Hashing Algorithms for Large-Scale Learning NIPS 2011
Efficient Methods for Overlapping Group Lasso NIPS 2011
Oracle inequalities for computationally budgeted model selection COLT 2011
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011
Learning to Locate Relative Outliers ACML 2011
Convergent Decomposition Solvers for Tree-reweighted Free Energies AISTATS 2011
Convex envelopes of complexity controlling penalties: the case against premature envelopment AISTATS 2011
Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization AISTATS 2011
Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011
Robust approachability and regret minimization in games with partial monitoring COLT 2011
Proximal Methods for Hierarchical Sparse Coding JMLR 2011
Two-Layer Multiple Kernel Learning AISTATS 2011