Skip to content
conftrace_

Sparse Optimization

241 papers

18
26
8
6
'10
'15
'20
'25

Papers

Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification NeurIPS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression NeurIPS 2010 Sparse Coding for Learning Interpretable Spatio-Temporal Primitives NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 Structured sparsity-inducing norms through submodular functions NeurIPS 2010 Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework NeurIPS 2010 A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds NeurIPS 2009 A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers NeurIPS 2009 Efficient Learning using Forward-Backward Splitting NeurIPS 2009 Fast Image Deconvolution using Hyper-Laplacian Priors NeurIPS 2009 Group Sparse Coding NeurIPS 2009 Heterogeneous multitask learning with joint sparsity constraints NeurIPS 2009 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Learning with Compressible Priors NeurIPS 2009 Nonparametric Greedy Algorithms for the Sparse Learning Problem NeurIPS 2009 Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis NeurIPS 2009 Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) NeurIPS 2009 Semi-supervised Learning using Sparse Eigenfunction Bases NeurIPS 2009 Sparse and Locally Constant Gaussian Graphical Models NeurIPS 2009 Sparse Estimation Using General Likelihoods and Non-Factorial Priors NeurIPS 2009 Sparse Metric Learning via Smooth Optimization NeurIPS 2009 Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation NeurIPS 2009 Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models NeurIPS 2008 An interior-point stochastic approximation method and an L1-regularized delta rule NeurIPS 2008