Copertina

Deep Learning without Global Optimization by Random Fourier Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Davis, Owen, Geraci, Gianluca, Motamed, Mohammad
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Numerical Analysis 65T40, 90C15, 65C05, 65C40, 60J22, 68T07
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Residual Multi-Fidelity Neural Network Computing
di: Davis, Owen, et al.
Pubblicazione: (2023)

On Kemeny's constant and stochastic complement
di: Bini, Dario Andrea, et al.
Pubblicazione: (2023)

Reaching the equilibrium: Long-term stable approximations for stochastic non-Newtonian Stokes equations with transport noise
di: Droniou, Jerome, et al.
Pubblicazione: (2024)

Fourier Residual Networks Achieve Spectral Accuracy for Discontinuous Functions
di: Davis, Owen, et al.
Pubblicazione: (2026)

FlexTrace: Exchangeable Randomized Trace Estimation for Matrix Functions
di: Madhavan, Madhusudan, et al.
Pubblicazione: (2026)

Deep neural networks can provably solve Bellman equations for Markov decision processes without the curse of dimensionality
di: Jentzen, Arnulf, et al.
Pubblicazione: (2025)

Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging
di: Narnhofer, Dominik, et al.
Pubblicazione: (2022)

Finite Sample Bounds for Sequential Monte Carlo and Adaptive Path Selection Using the $L_2$ Norm
di: Marion, Joe, et al.
Pubblicazione: (2018)

Spectral Gap of Metropolis Algorithms for Non-smooth Distributions under Isoperimetry
di: Liu, Shuigen, et al.
Pubblicazione: (2026)

Kemeny's constant minimization for reversible Markov chains via structure-preserving perturbations
di: Durastante, Fabio, et al.
Pubblicazione: (2025)

Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling
di: Klatzer, Teresa, et al.
Pubblicazione: (2023)

Convergence of kinetic Langevin samplers for non-convex potentials
di: Schuh, Katharina, et al.
Pubblicazione: (2024)

A Hybrid Iterative Neural Solver Based on Spectral Analysis for Parametric PDEs
di: Cui, Chen, et al.
Pubblicazione: (2024)

Convergence of Langevin AIS for multimodal distributions
di: Agarwal, Akshat, et al.
Pubblicazione: (2026)

A Representation Optimization Dichotomy, Lie-Algebraic Policy Optimization
di: KC, Sooraj, et al.
Pubblicazione: (2026)

Solving the Poisson equation using coupled Markov chains
di: Douc, Randal, et al.
Pubblicazione: (2022)

Reinforcement-learning-based Algorithms for Optimization Problems and Applications to Inverse Problems
di: Xu, Chen, et al.
Pubblicazione: (2023)

Convergence for adaptive resampling of random Fourier features
di: Huang, Xin, et al.
Pubblicazione: (2025)

Some Remarks on the Optimal Level of Randomization in Global Optimization
di: Theodosopoulos, Ted
Pubblicazione: (2004)

Deep Learning Based on Randomized Quasi-Monte Carlo Method for Solving Linear Kolmogorov Partial Differential Equation
di: Xiao, Jichang, et al.
Pubblicazione: (2023)

Variable Projected Augmented Lagrangian Methods for Generalized Lasso Problems
di: Aleotti, Stefano, et al.
Pubblicazione: (2025)

Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems
di: Klatzer, Teresa, et al.
Pubblicazione: (2025)

Learning to Integrate
di: Ernst, Oliver G., et al.
Pubblicazione: (2025)

An Inertial Langevin Algorithm
di: Falk, Alexander, et al.
Pubblicazione: (2025)

A probabilistic approach to spectral analysis of Cauchy-type inverse problems: Convergence and stability analysis
di: Cîmpean, Iulian, et al.
Pubblicazione: (2025)

Fisher entropic Fokker-Planck model of monatomic rarefied gases
di: Montanaro, Veronica, et al.
Pubblicazione: (2025)

Regularity and tailored regularization of Deep Neural Networks, with application to parametric PDEs in uncertainty quantification
di: Keller, Alexander, et al.
Pubblicazione: (2025)

Losing momentum in continuous-time stochastic optimisation
di: Jin, Kexin, et al.
Pubblicazione: (2022)

Reversibility of elliptical slice sampling revisited
di: Hasenpflug, Mareike, et al.
Pubblicazione: (2023)

On first passage time problems of Brownian motion -- The inverse method of images revisited
di: Christensen, Sören, et al.
Pubblicazione: (2024)

Optimal convergence rates of MCMC integration for functions with unbounded second moment
di: Hofstadler, Julian
Pubblicazione: (2024)

Rapid convergence of tempering chains to multimodal Gibbs measures
di: Son, Seungjae
Pubblicazione: (2026)

Function Approximation in Numerically Rank-Deficient Bases
di: Herremans, Astrid, et al.
Pubblicazione: (2025)

A Langevin sampling algorithm inspired by the Adam optimizer
di: Leimkuhler, Benedict, et al.
Pubblicazione: (2025)

Hadamard Langevin dynamics for sampling the l1-prior
di: Cheltsov, Ivan, et al.
Pubblicazione: (2024)

Numerical spectral analysis of Cauchy-type inverse problems: A probabilistic approach
di: Cîmpean, Iulian, et al.
Pubblicazione: (2024)

Time-complexity of sampling from a multimodal distribution using sequential Monte Carlo
di: Han, Ruiyu, et al.
Pubblicazione: (2025)

Convergence of a Sequential Monte Carlo algorithm towards multimodal distributions on Rd
di: Han, Ruiyu
Pubblicazione: (2025)

Mixing time of the conditional backward sampling particle filter
di: Karjalainen, Joona, et al.
Pubblicazione: (2023)

Convergence and non-asymptotic error analysis for kinetic Langevin samplers using the exact harmonic Langevin integrator
di: Schuh, Katharina
Pubblicazione: (2026)