Pages that link to "Item:Q128676"
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The following pages link to Smooth minimization of non-smooth functions (Q128676):
Displaying 50 items.
- Accelerated gradient boosting (Q2425242) (← links)
- Randomized first order algorithms with applications to \(\ell _{1}\)-minimization (Q2434980) (← links)
- On the \(O(1/t)\) convergence rate of the LQP prediction-correction method (Q2439520) (← links)
- Proximity point algorithm for low-rank matrix recovery from sparse noise corrupted data (Q2440136) (← links)
- Efficient algorithms for robust and stable principal component pursuit problems (Q2450901) (← links)
- Exact histogram specification for digital images using a variational approach (Q2513399) (← links)
- Bundle-level type methods uniformly optimal for smooth and nonsmooth convex optimization (Q2515032) (← links)
- Non-overlapping domain decomposition methods for dual total variation based image denoising (Q2515535) (← links)
- Introduction to the special issue -- Algorithmic game theory -- STOC/FOCS/SODA 2011 (Q2516241) (← links)
- Near-optimal no-regret algorithms for zero-sum games (Q2516247) (← links)
- Convex risk measures for portfolio optimization and concepts of flexibility (Q2576735) (← links)
- An optimal trade-off model for portfolio selection with sensitivity of parameters (Q2628195) (← links)
- The Moreau envelope based efficient first-order methods for sparse recovery (Q2628357) (← links)
- Large sparse signal recovery by conjugate gradient algorithm based on smoothing technique (Q2629501) (← links)
- An efficient inexact Newton-CG algorithm for the smallest enclosing ball problem of large dimensions (Q2630834) (← links)
- An efficient augmented Lagrangian method with applications to total variation minimization (Q2636603) (← links)
- Numerical methods for the resource allocation problem in a computer network (Q2662812) (← links)
- Robust Manhattan non-negative matrix factorization for image recovery and representation (Q2663487) (← links)
- First-order frameworks for continuous Newton-like dynamics governed by maximally monotone operators (Q2670974) (← links)
- Fast gradient methods for uniformly convex and weakly smooth problems (Q2673504) (← links)
- Nonsmooth rank-one matrix factorization landscape (Q2673521) (← links)
- Perturbed Fenchel duality and first-order methods (Q2687051) (← links)
- A simple nearly optimal restart scheme for speeding up first-order methods (Q2696573) (← links)
- On FISTA with a relative error rule (Q2696903) (← links)
- An abstract convergence framework with application to inertial inexact forward-backward methods (Q2696904) (← links)
- A smoothing proximal gradient algorithm with extrapolation for the relaxation of \({\ell_0}\) regularization problem (Q2696923) (← links)
- Fast convergence of inertial gradient dynamics with multiscale aspects (Q2696950) (← links)
- Nonconvex model for mixing noise with fractional-order regularization (Q2697362) (← links)
- NESTANets: stable, accurate and efficient neural networks for analysis-sparse inverse problems (Q2700171) (← links)
- Minimal realization and dynamic properties of optimal smoothers (Q2730281) (← links)
- Total Variation in Imaging (Q2789827) (← links)
- Fast inexact decomposition algorithms for large-scale separable convex optimization (Q2790883) (← links)
- Super-resolution of positive sources: the discrete setup (Q2797786) (← links)
- Complexity Certifications of First-Order Inexact Lagrangian Methods for General Convex Programming: Application to Real-Time MPC (Q2798546) (← links)
- Low Complexity Regularization of Linear Inverse Problems (Q2799919) (← links)
- An Introduction to Formally Real Jordan Algebras and Their Applications in Optimization (Q2802529) (← links)
- Projection Methods in Conic Optimization (Q2802538) (← links)
- An efficient inexact ABCD method for least squares semidefinite programming (Q2805705) (← links)
- An \(\mathcal O(1/{k})\) convergence rate for the variable stepsize Bregman operator splitting algorithm (Q2807288) (← links)
- Iteration complexity analysis of dual first-order methods for conic convex programming (Q2815553) (← links)
- Conditional gradient sliding for convex optimization (Q2816241) (← links)
- The rate of convergence of Nesterov's accelerated forward-backward method is actually faster than \(1/k^2\) (Q2817843) (← links)
- On convergence rate of distributed stochastic gradient algorithm for convex optimization with inequality constraints (Q2827487) (← links)
- A family of subgradient-based methods for convex optimization problems in a unifying framework (Q2829570) (← links)
- Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach (Q2830269) (← links)
- Optimization in high dimensions via accelerated, parallel, and proximal coordinate descent (Q2832112) (← links)
- A subgradient method for free material design (Q2832891) (← links)
- COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis (Q2867425) (← links)
- Primal–dual first-order methods for a class of cone programming (Q2867434) (← links)
- Proximal Splitting Methods in Signal Processing (Q2897282) (← links)
