Continuous Optimization

Stochastic Gradient Descent with Only One Projection NeurIPS 2012 Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NeurIPS 2012 Structured Sparse Canonical Correlation Analysis AISTATS 2012 Structured Sparsity via Alternating Direction Methods JMLR 2012 There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems AISTATS 2012 Variable Selection for Gaussian Graphical Models AISTATS 2012 Volume Regularization for Binary Classification NeurIPS 2012 A Fast Algorithm for Recovery of Jointly Sparse Vectors based on the Alternating Direction Methods AISTATS 2011 A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems AISTATS 2011 A Linear Approximation for Graph-based Simultaneous Localization and Mapping RSS 2011 A Non-Parametric Approach to Dynamic Programming NeurIPS 2011 A novel greedy algorithm for Nyström approximation AISTATS 2011 Approximate Model Selection for Large Scale LSSVM ACML 2011 Approximating Semidefinite Programs in Sublinear Time NeurIPS 2011 A Simpler Approach to Matrix Completion JMLR 2011 Automatic Calibration of Multiple Coplanar Sensors RSS 2011 Better Mini-Batch Algorithms via Accelerated Gradient Methods NeurIPS 2011 CAKE: Convex Adaptive Kernel Density Estimation AISTATS 2011 Can matrix coherence be efficiently and accurately estimated? AISTATS 2011 Clustered Multi-Task Learning Via Alternating Structure Optimization NeurIPS 2011 Concentration-Based Guarantees for Low-Rank Matrix Reconstruction COLT 2011 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Convergent Decomposition Solvers for Tree-reweighted Free Energies AISTATS 2011 Convex envelopes of complexity controlling penalties: the case against premature envelopment AISTATS 2011 Efficient variable selection in support vector machines via the alternating direction method of multipliers AISTATS 2011