Convex Optimization

Practical Large-Scale Optimization for Max-norm Regularization NeurIPS 2010 Random Conic Pursuit for Semidefinite Programming NeurIPS 2010 Relaxed Clipping: A Global Training Method for Robust Regression and Classification NeurIPS 2010 Robust PCA via Outlier Pursuit NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 Structured sparsity-inducing norms through submodular functions NeurIPS 2010 Throttling Poisson Processes NeurIPS 2010 t-logistic regression NeurIPS 2010 Accelerated Gradient Methods for Stochastic Optimization and Online Learning NeurIPS 2009 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NeurIPS 2009 A General Projection Property for Distribution Families NeurIPS 2009 Analysis of SVM with Indefinite Kernels NeurIPS 2009 An LP View of the M-best MAP problem NeurIPS 2009 Convex Relaxation of Mixture Regression with Efficient Algorithms NeurIPS 2009 Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NeurIPS 2009 Efficient Learning using Forward-Backward Splitting NeurIPS 2009 Efficient Recovery of Jointly Sparse Vectors NeurIPS 2009 Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming NeurIPS 2009 Fast Image Deconvolution using Hyper-Laplacian Priors NeurIPS 2009 Information-theoretic lower bounds on the oracle complexity of convex optimization NeurIPS 2009 Learning a Small Mixture of Trees NeurIPS 2009 On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NeurIPS 2009 On the Convergence of the Concave-Convex Procedure NeurIPS 2009 Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization NeurIPS 2009 An Extended Level Method for Efficient Multiple Kernel Learning NeurIPS 2008