Optimization & Theory

Periodic Step Size Adaptation for Single Pass On-line Learning NeurIPS 2009 Slow Learners are Fast NeurIPS 2009 A Massively Parallel Digital Learning Processor NeurIPS 2008 Deep Learning with Kernel Regularization for Visual Recognition NeurIPS 2008 Differentiable Sparse Coding NeurIPS 2008 Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance NeurIPS 2008 High-dimensional support union recovery in multivariate regression NeurIPS 2008 Learning with Consistency between Inductive Functions and Kernels NeurIPS 2008 Multi-stage Convex Relaxation for Learning with Sparse Regularization NeurIPS 2008 Nonparametric regression and classification with joint sparsity constraints NeurIPS 2008 PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning NeurIPS 2008 QUIC-SVD: Fast SVD Using Cosine Trees NeurIPS 2008 Regularized Learning with Networks of Features NeurIPS 2008 Regularized Policy Iteration NeurIPS 2008 A Spectral Regularization Framework for Multi-Task Structure Learning NeurIPS 2007 Classification via Minimum Incremental Coding Length (MICL) NeurIPS 2007 Near-Maximum Entropy Models for Binary Neural Representations of Natural Images NeurIPS 2007 Random Features for Large-Scale Kernel Machines NeurIPS 2007 Regularized Boost for Semi-Supervised Learning NeurIPS 2007 Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains NeurIPS 2007 Topmoumoute Online Natural Gradient Algorithm NeurIPS 2007 Blind Motion Deblurring Using Image Statistics NeurIPS 2006 Efficient sparse coding algorithms NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NeurIPS 2006