The following pages link to Lectures on convex optimization (Q723525):
Displaying 50 items.
- Fisher information regularization schemes for Wasserstein gradient flows (Q781954) (← links)
- A convex optimization approach to dynamic programming in continuous state and action spaces (Q831365) (← links)
- Introductory lectures on convex optimization. A basic course. (Q1417731) (← links)
- Regularization by architecture: a deep prior approach for inverse problems (Q1988362) (← links)
- Dimension-free Wasserstein contraction of nonlinear filters (Q2021415) (← links)
- Adjoint-based exact Hessian computation (Q2026361) (← links)
- A generalized worst-case complexity analysis for non-monotone line searches (Q2028039) (← links)
- Resource allocation for contingency planning: an inexact proximal bundle method for stochastic optimization (Q2030665) (← links)
- Asymptotic analysis of a structure-preserving integrator for damped Hamiltonian systems (Q2030822) (← links)
- Algorithms for nonnegative matrix factorization with the Kullback-Leibler divergence (Q2031873) (← links)
- Bounds for the tracking error of first-order online optimization methods (Q2032000) (← links)
- Minimizing uniformly convex functions by cubic regularization of Newton method (Q2032037) (← links)
- Computational semi-discrete optimal transport with general storage fees (Q2038176) (← links)
- Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems (Q2042418) (← links)
- A block inertial Bregman proximal algorithm for nonsmooth nonconvex problems with application to symmetric nonnegative matrix tri-factorization (Q2046565) (← links)
- Optimal step length for the Newton method: case of self-concordant functions (Q2067259) (← links)
- Adaptive optimization with periodic dither signals (Q2070015) (← links)
- Bregman primal-dual first-order method and application to sparse semidefinite programming (Q2070334) (← links)
- A piecewise conservative method for unconstrained convex optimization (Q2070340) (← links)
- A predictor-corrector affine scaling method to train optimized extreme learning machine (Q2071232) (← links)
- On stochastic mirror descent with interacting particles: convergence properties and variance reduction (Q2077867) (← links)
- Gaussian discrepancy: a probabilistic relaxation of vector balancing (Q2081474) (← links)
- Dualize, split, randomize: toward fast nonsmooth optimization algorithms (Q2082232) (← links)
- Curiosities and counterexamples in smooth convex optimization (Q2089782) (← links)
- A control-theoretic perspective on optimal high-order optimization (Q2089793) (← links)
- Manifold reconstruction and denoising from scattered data in high dimension (Q2095140) (← links)
- Optimization-based convex relaxations for nonconvex parametric systems of ordinary differential equations (Q2097651) (← links)
- Stochastic dual dynamic programming for multistage stochastic mixed-integer nonlinear optimization (Q2097671) (← links)
- On the convergence analysis of aggregated heavy-ball method (Q2104283) (← links)
- Network manipulation algorithm based on inexact alternating minimization (Q2109010) (← links)
- Discriminative clustering with representation learning with any ratio of labeled to unlabeled data (Q2114048) (← links)
- Accelerated proximal envelopes: application to componentwise methods (Q2116598) (← links)
- Adaptive Gauss-Newton method for solving systems of nonlinear equations (Q2116724) (← links)
- Convex optimization with inexact gradients in Hilbert space and applications to elliptic inverse problems (Q2117629) (← links)
- On the computational efficiency of catalyst accelerated coordinate descent (Q2117631) (← links)
- The generalized trust region subproblem: solution complexity and convex hull results (Q2118085) (← links)
- Distributed adaptive Newton methods with global superlinear convergence (Q2123229) (← links)
- Local convergence of tensor methods (Q2133417) (← links)
- Solution manifold and its statistical applications (Q2136611) (← links)
- Oracle complexity separation in convex optimization (Q2139268) (← links)
- Rates of superlinear convergence for classical quasi-Newton methods (Q2149549) (← links)
- On lower iteration complexity bounds for the convex concave saddle point problems (Q2149573) (← links)
- Status determination by interior-point methods for convex optimization problems in domain-driven form (Q2149574) (← links)
- A frequency-domain analysis of inexact gradient methods (Q2149575) (← links)
- Speed scaling scheduling of multiprocessor jobs with energy constraint and makespan criterion (Q2149611) (← links)
- Proportional-integral projected gradient method for conic optimization (Q2151872) (← links)
- Discrete processes and their continuous limits (Q2197184) (← links)
- Accelerated and unaccelerated stochastic gradient descent in model generality (Q2210408) (← links)
- Accelerated methods for saddle-point problem (Q2214606) (← links)
- Rapid evaluation of the spectral signal detection threshold and Stieltjes transform (Q2230693) (← links)
