Convex Optimization

Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012 No-Regret Algorithms for Unconstrained Online Convex Optimization NeurIPS 2012 Online Optimization with Gradual Variations COLT 2012 Optimal Regularized Dual Averaging Methods for Stochastic Optimization NeurIPS 2012 Perceptron Learning of SAT NeurIPS 2012 Proximal Newton-type methods for convex optimization NeurIPS 2012 Random Design Analysis of Ridge Regression COLT 2012 Recovery of Sparse Probability Measures via Convex Programming NeurIPS 2012 Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise JMLR 2012 Stochastic Gradient Descent with Only One Projection NeurIPS 2012 Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NeurIPS 2012 Structured Learning of Gaussian Graphical Models NeurIPS 2012 Submodular-Bregman and the Lovász-Bregman Divergences with Applications NeurIPS 2012 A Convergence Analysis of Log-Linear Training NeurIPS 2011 Algorithms and hardness results for parallel large margin learning NeurIPS 2011 Approximating Semidefinite Programs in Sublinear Time NeurIPS 2011 Better Mini-Batch Algorithms via Accelerated Gradient Methods NeurIPS 2011 Clustered Multi-Task Learning Via Alternating Structure Optimization NeurIPS 2011 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Convex envelopes of complexity controlling penalties: the case against premature envelopment AISTATS 2011 Efficient Methods for Overlapping Group Lasso NeurIPS 2011 Efficient Offline Communication Policies for Factored Multiagent POMDPs NeurIPS 2011 Finite-Time Regional Verification of Stochastic Nonlinear Systems RSS 2011 Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization AISTATS 2011 Greedy Algorithms for Structurally Constrained High Dimensional Problems NeurIPS 2011