:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kawamura, Yuya, Takabe, Satoshi
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2402.15125
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Convergence Acceleration of Markov Chain Monte Carlo-based Gradient Descent by Deep Unfolding
par: Hagiwara, Ryo, et autres
Publié: (2024)

Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer
par: Hagiwara, Ryo, et autres
Publié: (2025)

Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
par: Banerjee, Sayan, et autres
Publié: (2024)

Adaptive Kernel Selection for Stein Variational Gradient Descent
par: Melcher, Moritz, et autres
Publié: (2025)

Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient Descent
par: Della Libera, Luca, et autres
Publié: (2024)

Refined Gradient-Based Temperature Optimization for the Replica-Exchange Monte-Carlo Method
par: Miyata, Tatsuya, et autres
Publié: (2026)

Deep Unfolded Local Quantum Annealing
par: Arai, Shunta, et autres
Publié: (2024)

Finite-Particle Rates for Regularized Stein Variational Gradient Descent
par: He, Ye, et autres
Publié: (2026)

Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification
par: Tabor, Griffin, et autres
Publié: (2025)

Hubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detection
par: Takabe, Satoshi, et autres
Publié: (2023)

Condensed Stein Variational Gradient Descent for Uncertainty Quantification of Neural Networks
par: Padmanabha, Govinda Anantha, et autres
Publié: (2024)

Accelerated Gradient Descent for Faster Convergence with Minimal Overhead
par: Graca, Manuel, et autres
Publié: (2026)

Branching Stein Variational Gradient Descent for sampling multimodal distributions
par: Bañales, Isaías, et autres
Publié: (2025)

Accelerated Stein Variational Gradient Flow
par: Stein, Viktor, et autres
Publié: (2025)

Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
par: Mishkin, Aaron, et autres
Publié: (2024)

Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform Inversion
par: Corrales, Miguel, et autres
Publié: (2024)

Variational Stochastic Gradient Descent for Deep Neural Networks
par: Chen, Haotian, et autres
Publié: (2024)

Multirate Stein Variational Gradient Descent for Efficient Bayesian Sampling
par: Sarshar, Arash
Publié: (2026)

A Stein Gradient Descent Approach for Doubly Intractable Distributions
par: Lee, Heesang, et autres
Publié: (2024)

Stacking as Accelerated Gradient Descent
par: Agarwal, Naman, et autres
Publié: (2024)

The Blind Normalized Stein Variational Gradient Descent-Based Detection for Intelligent Random Access in Cellular IoT
par: Zhu, Xin, et autres
Publié: (2024)

On the Convergence Rate of LoRA Gradient Descent
par: Mu, Siqiao, et autres
Publié: (2025)

Regularized Stein Variational Gradient Flow
par: He, Ye, et autres
Publié: (2022)

Quantitative Local Convergence of Mean-Field Stein Variational Gradient Flow
par: Chizat, Lénaïc, et autres
Publié: (2026)

Anytime Acceleration of Gradient Descent
par: Zhang, Zihan, et autres
Publié: (2024)

Learning Provably Improves the Convergence of Gradient Descent
par: Song, Qingyu, et autres
Publié: (2025)

Convergence of Alternating Gradient Descent for Matrix Factorization
par: Ward, Rachel, et autres
Publié: (2023)

On the Convergence of Gradient Descent for Large Learning Rates
par: Crăciun, Alexandru, et autres
Publié: (2024)

Product-Stability: Provable Convergence for Gradient Descent on the Edge of Stability
par: Gan, Eric
Publié: (2026)

Convergence Analysis of Fractional Gradient Descent
par: Aggarwal, Ashwani
Publié: (2023)

Open Problem: Anytime Convergence Rate of Gradient Descent
par: Kornowski, Guy, et autres
Publié: (2024)

Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
par: Li, Tianyou, et autres
Publié: (2023)

On the Convergence of Gradient Descent on Learning Transformers with Residual Connections
par: Qin, Zhen, et autres
Publié: (2025)

Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes
par: Zhang, Ruiqi, et autres
Publié: (2025)

ELBOing Stein: Variational Bayes with Stein Mixture Inference
par: Rønning, Ola, et autres
Publié: (2024)

Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence
par: Deng, Yichuan, et autres
Publié: (2024)

Preconditioning for Accelerated Gradient Descent Optimization and Regularization
par: Ye, Qiang
Publié: (2024)

Streaming Krylov-Accelerated Stochastic Gradient Descent
par: Thomas, Stephen
Publié: (2025)

Increasing Batch Size Improves Convergence of Stochastic Gradient Descent with Momentum
par: Kamo, Keisuke, et autres
Publié: (2025)

Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region
par: Liang, Shuang, et autres
Publié: (2025)