Optimization

Optimization Problems for Fast AAM Fitting in-the-Wild ICCV 2013 Optimized Pedestrian Detection for Multiple and Occluded People CVPR 2013 Phase Retrieval using Alternating Minimization NeurIPS 2013 Supervised Sparse Analysis and Synthesis Operators NeurIPS 2013 Texture Enhanced Image Denoising via Gradient Histogram Preservation CVPR 2013 The Episolar Constraint: Monocular Shape from Shadow Correspondence CVPR 2013 When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements NeurIPS 2013 A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification AISTATS 2012 Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning NeurIPS 2012 Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization NeurIPS 2012 Krylov Subspace Descent for Deep Learning AISTATS 2012 Large Scale Distributed Deep Networks NeurIPS 2012 Proximal Newton-type methods for convex optimization NeurIPS 2012 Scaled Gradients on Grassmann Manifolds for Matrix Completion NeurIPS 2012 Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes NeurIPS 2012 A blind sparse deconvolution method for neural spike identification NeurIPS 2011 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NeurIPS 2011 Large-Scale Category Structure Aware Image Categorization NeurIPS 2011 An analysis on negative curvature induced by singularity in multi-layer neural-network learning NeurIPS 2010 Parallelized Stochastic Gradient Descent NeurIPS 2010 Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake NeurIPS 2010 Heavy-Tailed Symmetric Stochastic Neighbor Embedding NeurIPS 2009 Periodic Step Size Adaptation for Single Pass On-line Learning NeurIPS 2009 A Massively Parallel Digital Learning Processor NeurIPS 2008