Copertina

Faster Computation of Entropic Optimal Transport via Stable Low Frequency Modes

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chhaibi, Reda, Gratton, Serge, Vaiter, Samuel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Numerical Analysis Optimization and Control Probability Computation Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Constrained Density Estimation via Optimal Transport
di: Hu, Yinan, et al.
Pubblicazione: (2026)

Stochastic Optimal Control Matching
di: Domingo-Enrich, Carles, et al.
Pubblicazione: (2023)

Dual Block Gradient Ascent for Entropically Regularised Quantum Optimal Transport
di: Randig, Marvin, et al.
Pubblicazione: (2025)

DeepMartingale: Duality of the Optimal Stopping Problem with Expressivity and High-Dimensional Hedging
di: Ye, Junyan, et al.
Pubblicazione: (2025)

Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient
di: Lim, Dong-Young, et al.
Pubblicazione: (2022)

Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
di: Liang, Luxu, et al.
Pubblicazione: (2024)

Nonparametric Filtering, Estimation and Classification using Neural Jump ODEs
di: Heiss, Jakob, et al.
Pubblicazione: (2024)

Generalization Bounds for Sparse Random Feature Expansions
di: Hashemi, Abolfazl, et al.
Pubblicazione: (2021)

On Bellman equations for continuous-time policy evaluation I: discretization and approximation
di: Mou, Wenlong, et al.
Pubblicazione: (2024)

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs
di: Furuya, Takashi, et al.
Pubblicazione: (2024)

Neural Operators Can Play Dynamic Stackelberg Games
di: Alvarez, Guillermo, et al.
Pubblicazione: (2024)

Provably Faster Gradient Descent via Long Steps
di: Grimmer, Benjamin
Pubblicazione: (2023)

Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
di: Srinivasan, Vishwak, et al.
Pubblicazione: (2025)

Control, Optimal Transport and Neural Differential Equations in Supervised Learning
di: Phung, Minh-Nhat, et al.
Pubblicazione: (2025)

Global Regularity Estimates for Optimal Transport via Entropic Regularisation
di: Gozlan, Nathael, et al.
Pubblicazione: (2025)

Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems
di: Karris, Nicholas, et al.
Pubblicazione: (2024)

Faster Randomized Methods for Orthogonality Constrained Problems
di: Shustin, Boris, et al.
Pubblicazione: (2021)

Beyond Muon: MUD (MomentUm Decorrelation) for Faster Transformer Training
di: Southworth, Ben S., et al.
Pubblicazione: (2026)

Solving Elliptic Optimal Control Problems via Neural Networks and Optimality System
di: Dai, Yongcheng, et al.
Pubblicazione: (2023)

Assigning Stationary Distributions to Sparse Stochastic Matrices
di: Gillis, Nicolas, et al.
Pubblicazione: (2023)

Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis
di: Bartl, Daniel, et al.
Pubblicazione: (2024)

Entropic Selection Principle for Monge's Optimal Transport
di: Aryan, Shrey, et al.
Pubblicazione: (2025)

On Approximate Computation of Critical Points
di: Ahmadi, Amir Ali, et al.
Pubblicazione: (2026)

Contributions to Robust and Efficient Methods for Analysis of High Dimensional Data
di: Yang, Kai
Pubblicazione: (2025)

A Unified Framework from Boltzmann Transport to Proton Treatment Planning
di: Kyprianou, Andreas E., et al.
Pubblicazione: (2025)

Provably convergent stochastic fixed-point algorithm for free-support Wasserstein barycenter of continuous non-parametric measures
di: Chen, Zeyi, et al.
Pubblicazione: (2025)

Non-exchangeable evolutionary and mean field games and their applications
di: Yoshioka, H., et al.
Pubblicazione: (2025)

Numerical method for approximately optimal solutions of two-stage distributionally robust optimization with marginal constraints
di: Neufeld, Ariel, et al.
Pubblicazione: (2022)

Numerical method for feasible and approximately optimal solutions of multi-marginal optimal transport beyond discrete measures
di: Neufeld, Ariel, et al.
Pubblicazione: (2022)

A New Look at the Ensemble Kalman Filter for Inverse Problems: Duality, Non-Asymptotic Analysis and Convergence Acceleration
di: Krishnanunni, C G, et al.
Pubblicazione: (2026)

Error analysis for stochastic gradient optimization schemes using modified equations
di: Bréhier, Charles-Edouard, et al.
Pubblicazione: (2024)

Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms
di: Ha, Yunsoo, et al.
Pubblicazione: (2024)

Deep learning algorithms for FBSDEs with jumps: Applications to option pricing and a MFG model for smart grids
di: Alasseur, Clémence, et al.
Pubblicazione: (2024)

Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line
di: Hertrich, Johannes, et al.
Pubblicazione: (2023)

Feasible approximation of matching equilibria for large-scale matching for teams problems
di: Neufeld, Ariel, et al.
Pubblicazione: (2023)

Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels
di: Hertrich, Johannes, et al.
Pubblicazione: (2022)

Linking PageRank, Time Reversal, and Policy Evaluation
di: Avrachenkov, Konstantin, et al.
Pubblicazione: (2026)

Multi-level Optimal Control with Neural Surrogate Models
di: Kalise, Dante, et al.
Pubblicazione: (2024)

Method of Successive Approximations for Stochastic Optimal Control: Contractivity and Convergence
di: Taoufik, Safouane, et al.
Pubblicazione: (2024)

Solving Dense Linear Systems Faster Than via Preconditioning
di: Dereziński, Michał, et al.
Pubblicazione: (2023)