The following pages link to Learning with Structured Sparsity (Q5396730):
Displaying 41 items.
- Smooth sparse coding via marginal regression for learning sparse representations (Q309913) (← links)
- Grouping strategies and thresholding for high dimensional linear models (Q394551) (← links)
- Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset (Q518124) (← links)
- Comment on: \(\ell _{1}\)-penalization for mixture regression models (Q619143) (← links)
- Structured, sparse regression with application to HIV drug resistance (Q641120) (← links)
- Foveated compressed sensing (Q736494) (← links)
- Convex relaxations of penalties for sparse correlated variables with bounded total variation (Q747277) (← links)
- Theoretical guarantees for graph sparse coding (Q778037) (← links)
- Linearized alternating direction method of multipliers for sparse group and fused Lasso models (Q1623671) (← links)
- Two-level structural sparsity regularization for identifying lattices and defects in noisy images (Q1647620) (← links)
- Robust visual tracking via consistent low-rank sparse learning (Q1799927) (← links)
- Structured learning with constrained conditional models (Q1945119) (← links)
- Sequential approaches for learning datum-wise sparse representations (Q1945129) (← links)
- Regularizers for structured sparsity (Q1949299) (← links)
- Theoretical properties of the overlapping groups Lasso (Q1950815) (← links)
- Traditional and recent approaches in background modeling for foreground detection: an overview (Q2015048) (← links)
- Beyond covariance: SICE and kernel based visual feature representation (Q2056438) (← links)
- On change-point estimation under Sobolev sparsity (Q2180074) (← links)
- Efficient inexact proximal gradient algorithms for structured sparsity-inducing norm (Q2185635) (← links)
- Cluster sparsity field: an internal hyperspectral imagery prior for reconstruction (Q2200022) (← links)
- Discrete optimization methods for group model selection in compressed sensing (Q2235146) (← links)
- Sparse trace norm regularization (Q2259743) (← links)
- Investigating consumers' store-choice behavior via hierarchical variable selection (Q2324251) (← links)
- Learning Reductions to Sparse Sets (Q2849914) (← links)
- Designing Structured Sparse Dictionaries for Sparse Representation Modeling (Q3020508) (← links)
- Structured Sparsity: Discrete and Convex Approaches (Q3460840) (← links)
- Sparsity Constrained Estimation in Image Processing and Computer Vision (Q4556987) (← links)
- Learning Sparsifying Transforms (Q4578417) (← links)
- Learning the Structure for Structured Sparsity (Q4580804) (← links)
- (Q4637069) (← links)
- ORKA: Object reconstruction using a K-approximation graph (Q5058112) (← links)
- Structured sparse support vector machine with ordered features (Q5073382) (← links)
- Overlapping group lasso for high-dimensional generalized linear models (Q5076945) (← links)
- (Q5129275) (← links)
- (Q5214174) (← links)
- Sparse low-rank separated representation models for learning from data (Q5243616) (← links)
- Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery (Q5380402) (← links)
- Deep Learning as Sparsity-Enforcing Algorithms (Q5879781) (← links)
- Structured sparsity through convex optimization (Q5965303) (← links)
- Learning sparse linear combinations of basis functions over a finite domain (Q6083907) (← links)
- An improved tensor regression model via location smoothing (Q6541789) (← links)
