On The Convergence of Euler Discretization of Finite-Time Convergent Gradient Flows
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhang, Siqi, Benosman, Mouhacine, Romero, Orlando |
|---|---|
| Formato: | Preprint |
| Publicado: |
2020
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Constrained Diffusion Models for Synthesizing Representative Power Flow Datasets
por: Hoseinpour, Milad, et al.
Publicado: (2025)
por: Hoseinpour, Milad, et al.
Publicado: (2025)
Reinforcement learning-based estimation for partial differential equations
por: Mowlavi, Saviz, et al.
Publicado: (2023)
por: Mowlavi, Saviz, et al.
Publicado: (2023)
Quantitative Convergence of Wasserstein Gradient Flows of Kernel Mean Discrepancies
por: Chizat, Lénaïc, et al.
Publicado: (2026)
por: Chizat, Lénaïc, et al.
Publicado: (2026)
Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
por: Castin, Valérie, et al.
Publicado: (2026)
por: Castin, Valérie, et al.
Publicado: (2026)
Convergence of Continuous Normalizing Flows for Learning Probability Distributions
por: Gao, Yuan, et al.
Publicado: (2024)
por: Gao, Yuan, et al.
Publicado: (2024)
Physics-Guided Recurrent State-Space Neural Networks for Multi-Step Prediction
por: Li, Ruiyuan, et al.
Publicado: (2026)
por: Li, Ruiyuan, et al.
Publicado: (2026)
Learning Sampled-data Control for Swarms via MeanFlow
por: Dong, Anqi, et al.
Publicado: (2026)
por: Dong, Anqi, et al.
Publicado: (2026)
Generative modeling of conditional probability distributions on the level-sets of collective variables
por: Akhyar, Fatima-Zahrae, et al.
Publicado: (2025)
por: Akhyar, Fatima-Zahrae, et al.
Publicado: (2025)
Directional Convergence, Benign Overfitting of Gradient Descent in leaky ReLU two-layer Neural Networks
por: Hashimoto, Ichiro
Publicado: (2025)
por: Hashimoto, Ichiro
Publicado: (2025)
Edge-based Parametric Digital Twins for Intelligent Building Indoor Climate Modeling
por: Ni, Zhongjun, et al.
Publicado: (2024)
por: Ni, Zhongjun, et al.
Publicado: (2024)
Exact Sequence Interpolation with Transformers
por: Alcalde, Albert, et al.
Publicado: (2025)
por: Alcalde, Albert, et al.
Publicado: (2025)
On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers
por: Štrupl, Miroslav, et al.
Publicado: (2025)
por: Štrupl, Miroslav, et al.
Publicado: (2025)
Input Convex Kolmogorov Arnold Networks
por: Deschatre, Thomas, et al.
Publicado: (2025)
por: Deschatre, Thomas, et al.
Publicado: (2025)
Nesterov acceleration despite very noisy gradients
por: Gupta, Kanan, et al.
Publicado: (2023)
por: Gupta, Kanan, et al.
Publicado: (2023)
Data-Driven Approach for Accelerating Selective Harmonic Elimination Algorithm in Parallel Power Converters
por: Karimi, E., et al.
Publicado: (2024)
por: Karimi, E., et al.
Publicado: (2024)
A Generalization Bound for a Family of Implicit Networks
por: Fung, Samy Wu, et al.
Publicado: (2024)
por: Fung, Samy Wu, et al.
Publicado: (2024)
Safety Margins for Reinforcement Learning
por: Grushin, Alexander, et al.
Publicado: (2023)
por: Grushin, Alexander, et al.
Publicado: (2023)
Criticality and Safety Margins for Reinforcement Learning
por: Grushin, Alexander, et al.
Publicado: (2024)
por: Grushin, Alexander, et al.
Publicado: (2024)
Super-fast Rates of Convergence for Neural Network Classifiers under the Hard Margin Condition
por: Tepakbong, Nathanael, et al.
Publicado: (2025)
por: Tepakbong, Nathanael, et al.
Publicado: (2025)
Non-Asymptotic Convergence of Discrete Diffusion Models: Masked and Random Walk dynamics
por: Conforti, Giovanni, et al.
Publicado: (2025)
por: Conforti, Giovanni, et al.
Publicado: (2025)
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
por: Zhang, Xiangyuan, et al.
Publicado: (2023)
por: Zhang, Xiangyuan, et al.
Publicado: (2023)
Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing
por: Yi, Zeji, et al.
Publicado: (2026)
por: Yi, Zeji, et al.
Publicado: (2026)
Knowledge Integration in Differentiable Models: A Comparative Study of Data-Driven, Soft-Constrained, and Hard-Constrained Paradigms for Identification and Control of the Single Machine Infinite Bus System
por: Kang, Shinhoo, et al.
Publicado: (2026)
por: Kang, Shinhoo, et al.
Publicado: (2026)
BP(λ): Online Learning via Synthetic Gradients
por: Pemberton, Joseph, et al.
Publicado: (2024)
por: Pemberton, Joseph, et al.
Publicado: (2024)
Convergence of gradient descent for deep neural networks
por: Chatterjee, Sourav
Publicado: (2022)
por: Chatterjee, Sourav
Publicado: (2022)
Flow matching on homogeneous spaces
por: Ruscelli, Francesco
Publicado: (2026)
por: Ruscelli, Francesco
Publicado: (2026)
Tracking Finite-Time Lyapunov Exponents to Robustify Neural ODEs
por: Wöhrer, Tobias, et al.
Publicado: (2026)
por: Wöhrer, Tobias, et al.
Publicado: (2026)
Graph-Conditional Flow Matching for Relational Data Generation
por: Scassola, Davide, et al.
Publicado: (2025)
por: Scassola, Davide, et al.
Publicado: (2025)
Generative Design of Ship Propellers using Conditional Flow Matching
por: Kruger, Patrick, et al.
Publicado: (2026)
por: Kruger, Patrick, et al.
Publicado: (2026)
Matryoshka Policy Gradient for Entropy-Regularized RL: Convergence and Global Optimality
por: Ged, François, et al.
Publicado: (2023)
por: Ged, François, et al.
Publicado: (2023)
Tracking the Median of Gradients with a Stochastic Proximal Point Method
por: Schaipp, Fabian, et al.
Publicado: (2024)
por: Schaipp, Fabian, et al.
Publicado: (2024)
Diagonal Linear Networks and the Lasso Regularization Path
por: Berthier, Raphaël
Publicado: (2025)
por: Berthier, Raphaël
Publicado: (2025)
Explicit neural network classifiers for non-separable data
por: Ewald, Patrícia Muñoz
Publicado: (2025)
por: Ewald, Patrícia Muñoz
Publicado: (2025)
An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
por: Saini, Saurabh, et al.
Publicado: (2026)
por: Saini, Saurabh, et al.
Publicado: (2026)
Convergence of the Stochastic Heavy Ball Method With Approximate Gradients and/or Block Updating
por: Tadipatri, Uday Kiran Reddy, et al.
Publicado: (2023)
por: Tadipatri, Uday Kiran Reddy, et al.
Publicado: (2023)
Clustering in pure-attention hardmax transformers and its role in sentiment analysis
por: Alcalde, Albert, et al.
Publicado: (2024)
por: Alcalde, Albert, et al.
Publicado: (2024)
Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization
por: Jeong, Halyun, et al.
Publicado: (2025)
por: Jeong, Halyun, et al.
Publicado: (2025)
On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime
por: Jiang, Shuai, et al.
Publicado: (2026)
por: Jiang, Shuai, et al.
Publicado: (2026)
Gradient descent provably escapes saddle points in the training of shallow ReLU networks
por: Cheridito, Patrick, et al.
Publicado: (2022)
por: Cheridito, Patrick, et al.
Publicado: (2022)
Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks
por: Lam, Samuel Chun-Hei, et al.
Publicado: (2025)
por: Lam, Samuel Chun-Hei, et al.
Publicado: (2025)
Ejemplares similares
-
Constrained Diffusion Models for Synthesizing Representative Power Flow Datasets
por: Hoseinpour, Milad, et al.
Publicado: (2025) -
Reinforcement learning-based estimation for partial differential equations
por: Mowlavi, Saviz, et al.
Publicado: (2023) -
Quantitative Convergence of Wasserstein Gradient Flows of Kernel Mean Discrepancies
por: Chizat, Lénaïc, et al.
Publicado: (2026) -
Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
por: Castin, Valérie, et al.
Publicado: (2026) -
Convergence of Continuous Normalizing Flows for Learning Probability Distributions
por: Gao, Yuan, et al.
Publicado: (2024)