Wasserstein gradient flow for optimal probability measure decomposition
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Jiangze, Ryan, Christopher Thomas, Tong, Xin T. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Optimizing for Strategy Diversity in the Design of Video Games
by: Hanguir, Oussama, et al.
Published: (2021)
by: Hanguir, Oussama, et al.
Published: (2021)
A second-order-like optimizer with adaptive gradient scaling for deep learning
by: Bolte, Jérôme, et al.
Published: (2024)
by: Bolte, Jérôme, et al.
Published: (2024)
Robust personalized pricing under uncertainty of purchase probabilities
by: Ikeda, Shunnosuke, et al.
Published: (2024)
by: Ikeda, Shunnosuke, et al.
Published: (2024)
Pickup & Delivery with Time Windows and Transfers: combining decomposition with metaheuristics
by: Avgerinos, Ioannis, et al.
Published: (2025)
by: Avgerinos, Ioannis, et al.
Published: (2025)
When majority rules, minority loses: bias amplification of gradient descent
by: Bachoc, François, et al.
Published: (2025)
by: Bachoc, François, et al.
Published: (2025)
Remarks on the Polyak-Lojasiewicz inequality and the convergence of gradient systems
by: de Oliveira, Arthur Castello B., et al.
Published: (2025)
by: de Oliveira, Arthur Castello B., et al.
Published: (2025)
Muon Dynamics as a Spectral Wasserstein Flow
by: Peyré, Gabriel
Published: (2026)
by: Peyré, Gabriel
Published: (2026)
Employing Deep Neural Operators for PDE control by decoupling training and optimization
by: Lundqvist, Oliver G. S., et al.
Published: (2025)
by: Lundqvist, Oliver G. S., et al.
Published: (2025)
Layerwise goal-oriented adaptivity for neural ODEs: an optimal control perspective
by: Hintermüller, Michael, et al.
Published: (2026)
by: Hintermüller, Michael, et al.
Published: (2026)
Feasible Pairings for Decentralized Integral Controllability of Non-Square Systems
by: Tong, Yuhao, et al.
Published: (2026)
by: Tong, Yuhao, et al.
Published: (2026)
A deep learning method for solving stochastic optimal control problems driven by fully-coupled FBSDEs
by: Ji, Shaolin, et al.
Published: (2022)
by: Ji, Shaolin, et al.
Published: (2022)
Mixed variable structural optimization using mixed variable system Monte Carlo tree search formulation
by: Ko, Fu-Yao, et al.
Published: (2023)
by: Ko, Fu-Yao, et al.
Published: (2023)
Constrained Sliced Wasserstein Embedding
by: NaderiAlizadeh, Navid, et al.
Published: (2025)
by: NaderiAlizadeh, Navid, et al.
Published: (2025)
A robust optimization approach to flow decomposition
by: Stinzendörfer, Moritz, et al.
Published: (2024)
by: Stinzendörfer, Moritz, et al.
Published: (2024)
Enhancing kidney transplantation through multi-agent kidney exchange programs: A comprehensive review and optimization models
by: Sharifi, Shayan
Published: (2025)
by: Sharifi, Shayan
Published: (2025)
Energy Management for Renewable-Colocated Artificial Intelligence Data Centers
by: Li, Siying, et al.
Published: (2025)
by: Li, Siying, et al.
Published: (2025)
Sticky-reflecting diffusion as a Wasserstein gradient flow
by: Casteras, Jean-Baptiste, et al.
Published: (2024)
by: Casteras, Jean-Baptiste, et al.
Published: (2024)
Exact alternative optima for nonlinear optimization problems defined with maximum component objective function constrained by the Sugeno-Weber fuzzy relational inequalities
by: Ghodousian, Amin, et al.
Published: (2025)
by: Ghodousian, Amin, et al.
Published: (2025)
Offline Supervised Learning V.S. Online Direct Policy Optimization: A Comparative Study and A Unified Training Paradigm for Neural Network-Based Optimal Feedback Control
by: Zhao, Yue, et al.
Published: (2022)
by: Zhao, Yue, et al.
Published: (2022)
Recurrent neural networks: vanishing and exploding gradients are not the end of the story
by: Zucchet, Nicolas, et al.
Published: (2024)
by: Zucchet, Nicolas, et al.
Published: (2024)
A physics-informed Bayesian optimization method for rapid development of electrical machines
by: Asef, Pedram, et al.
Published: (2025)
by: Asef, Pedram, et al.
Published: (2025)
Precise gradient descent training dynamics for finite-width multi-layer neural networks
by: Han, Qiyang, et al.
Published: (2025)
by: Han, Qiyang, et al.
Published: (2025)
Robust $Q$-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty
by: Neufeld, Ariel, et al.
Published: (2022)
by: Neufeld, Ariel, et al.
Published: (2022)
Tutorial on amortized optimization
by: Amos, Brandon
Published: (2022)
by: Amos, Brandon
Published: (2022)
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2022)
by: Ding, Dongsheng, et al.
Published: (2022)
The Wasserstein gradient flow of the Sinkhorn divergence between Gaussian distributions
by: Hardion, Mathis, et al.
Published: (2026)
by: Hardion, Mathis, et al.
Published: (2026)
Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity
by: Yang, Yan, et al.
Published: (2024)
by: Yang, Yan, et al.
Published: (2024)
Unregularized limit of stochastic gradient method for Wasserstein distributionally robust optimization
by: Le, Tam
Published: (2025)
by: Le, Tam
Published: (2025)
Algorithmic Prompt-Augmentation for Efficient LLM-Based Heuristic Design for A* Search
by: Bömer, Thomas, et al.
Published: (2026)
by: Bömer, Thomas, et al.
Published: (2026)
FMIP: Joint Continuous-Integer Flow For Mixed-Integer Linear Programming
by: Li, Hongpei, et al.
Published: (2025)
by: Li, Hongpei, et al.
Published: (2025)
Topology optimization concerning the mass distribution via filtered gradient flows on the Wasserstein space
by: Okazaki, Fumiya, et al.
Published: (2026)
by: Okazaki, Fumiya, et al.
Published: (2026)
Diffeomorphic interpolation for efficient persistence-based topological optimization
by: Carriere, Mathieu, et al.
Published: (2024)
by: Carriere, Mathieu, et al.
Published: (2024)
Fuzzy hyperparameters update in a second order optimization
by: Bensadok, Abdelaziz, et al.
Published: (2024)
by: Bensadok, Abdelaziz, et al.
Published: (2024)
Introduction to optimization methods for training SciML models
by: Kopaničáková, Alena, et al.
Published: (2026)
by: Kopaničáková, Alena, et al.
Published: (2026)
Stochastic Inverse Problem: stability, regularization and Wasserstein gradient flow
by: Li, Qin, et al.
Published: (2024)
by: Li, Qin, et al.
Published: (2024)
Efficient sparse probability measures recovery via Bregman gradient
by: Pan, Jianting, et al.
Published: (2024)
by: Pan, Jianting, et al.
Published: (2024)
High-order expansion of Neural Ordinary Differential Equations flows
by: Izzo, Dario, et al.
Published: (2025)
by: Izzo, Dario, et al.
Published: (2025)
Linear attention is (maybe) all you need (to understand transformer optimization)
by: Ahn, Kwangjun, et al.
Published: (2023)
by: Ahn, Kwangjun, et al.
Published: (2023)
Frugality in second-order optimization: floating-point approximations for Newton's method
by: Carrino, Giuseppe, et al.
Published: (2025)
by: Carrino, Giuseppe, et al.
Published: (2025)
Deep learning enhanced mixed integer optimization: Learning to reduce model dimensionality
by: Triantafyllou, Niki, et al.
Published: (2024)
by: Triantafyllou, Niki, et al.
Published: (2024)
Similar Items
-
Optimizing for Strategy Diversity in the Design of Video Games
by: Hanguir, Oussama, et al.
Published: (2021) -
A second-order-like optimizer with adaptive gradient scaling for deep learning
by: Bolte, Jérôme, et al.
Published: (2024) -
Robust personalized pricing under uncertainty of purchase probabilities
by: Ikeda, Shunnosuke, et al.
Published: (2024) -
Pickup & Delivery with Time Windows and Transfers: combining decomposition with metaheuristics
by: Avgerinos, Ioannis, et al.
Published: (2025) -
When majority rules, minority loses: bias amplification of gradient descent
by: Bachoc, François, et al.
Published: (2025)