The following pages link to (Q5396698):
Displaying 27 items.
- Bayesian variable selection and estimation for group Lasso (Q273646) (← links)
- Gradient sliding for composite optimization (Q312670) (← links)
- A lasso for hierarchical interactions (Q366961) (← links)
- Correlated topographic analysis: estimating an ordering of correlated components (Q374131) (← links)
- Smoothing proximal gradient method for general structured sparse regression (Q439167) (← links)
- Proximal methods for the latent group lasso penalty (Q457209) (← links)
- Estimates on compressed neural networks regression (Q889370) (← links)
- Inexact proximal stochastic gradient method for convex composite optimization (Q1694394) (← links)
- Image deblurring with coupled dictionary learning (Q1799986) (← links)
- Fast projections onto mixed-norm balls with applications (Q1944995) (← links)
- Generalized stochastic Frank-Wolfe algorithm with stochastic ``substitute'' gradient for structured convex optimization (Q2020608) (← links)
- Acceleration techniques for level bundle methods in weakly smooth convex constrained optimization (Q2023658) (← links)
- A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives (Q2165600) (← links)
- Estimating piecewise monotone signals (Q2180071) (← links)
- Efficient inexact proximal gradient algorithms for structured sparsity-inducing norm (Q2185635) (← links)
- Optimization problems involving group sparsity terms (Q2330642) (← links)
- Learning with optimal interpolation norms (Q2420165) (← links)
- Modular proximal optimization for multidimensional total-variation regularization (Q4614088) (← links)
- A First-Order Optimization Algorithm for Statistical Learning with Hierarchical Sparsity Structure (Q5086011) (← links)
- On a Reduction for a Class of Resource Allocation Problems (Q5087712) (← links)
- (Q5148950) (← links)
- Simultaneous Estimation of Nongaussian Components and Their Correlation Structure (Q5380858) (← links)
- Structured sparsity through convex optimization (Q5965303) (← links)
- Optimal Methods for Convex Risk-Averse Distributed Optimization (Q6116242) (← links)
- Using Taylor-approximated gradients to improve the Frank-Wolfe method for empirical risk minimization (Q6579995) (← links)
- Structured learning in time-dependent Cox models (Q6618308) (← links)
- Efficient path algorithms for clustered Lasso and OSCAR (Q6670096) (← links)
