Sparse Optimization
241 papers
Papers per year
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5
10
16
18
15
13
21
20
26
11
7
9
10
8
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14
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7
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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