:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Zifan, Dong, Anqi, Selim, Mahmoud, Zavlanos, Michael M., Johansson, Karl H.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2509.21250
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Source-Guided Flow Matching
by: Wang, Zifan, et al.
Published: (2025)

Distributionally Robust Federated Learning with Outlier Resilience
by: Wang, Zifan, et al.
Published: (2025)

Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
by: Wang, Zifan, et al.
Published: (2026)

Wasserstein Distributionally Robust Nash Equilibrium Seeking with Heterogeneous Data: A Lagrangian Approach
by: Wang, Zifan, et al.
Published: (2025)

Risk-averse Learning with Non-Stationary Distributions
by: Wang, Siyi, et al.
Published: (2024)

Group Distributionally Robust Machine Learning under Group Level Distributional Uncertainty
by: Konti, Xenia, et al.
Published: (2025)

Risk-Averse Learning with Varying Risk Levels
by: Wang, Siyi, et al.
Published: (2025)

Learning Sampled-data Control for Swarms via MeanFlow
by: Dong, Anqi, et al.
Published: (2026)

Distributionally Robust Clustered Federated Learning: A Case Study in Healthcare
by: Konti, Xenia, et al.
Published: (2024)

OAT-FM: Optimal Acceleration Transport for Improved Flow Matching
by: Yue, Angxiao, et al.
Published: (2025)

First- and Zeroth-Order Learning in Asynchronous Games
by: Wang, Zifan, et al.
Published: (2025)

Learning of Nash Equilibria in Risk-Averse Games
by: Wang, Zifan, et al.
Published: (2024)

Risk-averse learning with delayed feedback
by: Wang, Siyi, et al.
Published: (2024)

Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits
by: Shen, Yi, et al.
Published: (2023)

Projected Gradient Descent for Constrained Decision-Dependent Optimization
by: Wang, Zifan, et al.
Published: (2025)

Asymmetric Feedback Learning in Online Convex Games
by: Wang, Zifan, et al.
Published: (2023)

Enhancing Privacy in Federated Learning through Local Training
by: Bastianello, Nicola, et al.
Published: (2024)

Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?
by: Riess, Hans, et al.
Published: (2024)

Achieving Linear Speedup for Composite Federated Learning
by: Huang, Kun, et al.
Published: (2026)

Policy Evaluation in Distributional LQR (Extended Version)
by: Wang, Zifan, et al.
Published: (2023)

Control Synthesis from Linear Temporal Logic Specifications using Model-Free Reinforcement Learning
by: Bozkurt, Alper Kamil, et al.
Published: (2019)

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport
by: Liu, Pengxi, et al.
Published: (2025)

Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
by: Liu, Guangyi, et al.
Published: (2025)

Learning Optimal Strategies for Temporal Tasks in Stochastic Games
by: Bozkurt, Alper Kamil, et al.
Published: (2021)

Hierarchical Federated ADMM
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2024)

Federated Hierarchical Reinforcement Learning for Adaptive Traffic Signal Control
by: Fu, Yongjie, et al.
Published: (2025)

Transfer Reinforcement Learning in Heterogeneous Action Spaces using Subgoal Mapping
by: Sivakumar, Kavinayan P., et al.
Published: (2024)

Coupled Flow Matching
by: Cai, Wenxi, et al.
Published: (2025)

Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy
by: Huo, Wei, et al.
Published: (2024)

Byzantine-Robust Federated Learning with Learnable Aggregation Weights
by: Parsa, Javad, et al.
Published: (2025)

Personalized Federated Learning under Model Dissimilarity Constraints
by: Erickson, Samuel, et al.
Published: (2025)

Active Flow Matching
by: Grewal, Yashvir S., et al.
Published: (2026)

Low-Pass Flow Matching
by: Ruscio, Francesco M., et al.
Published: (2026)

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
by: Zhang, Junru, et al.
Published: (2026)

Explicit Flow Matching: On The Theory of Flow Matching Algorithms with Applications
by: Ryzhakov, Gleb, et al.
Published: (2024)

Iterative Training of Physics-Informed Neural Networks with Fourier-enhanced Features
by: Wu, Yulun, et al.
Published: (2025)

Inverse Reinforcement Learning from Non-Stationary Learning Agents
by: Sivakumar, Kavinayan P., et al.
Published: (2024)

Real-time Hybrid System Identification with Online Deterministic Annealing
by: Mavridis, Christos, et al.
Published: (2024)

Bures-Wasserstein Flow Matching for Graph Generation
by: Jiang, Keyue, et al.
Published: (2025)

Flow Matching on Lie Groups
by: Sherry, Finn M., et al.
Published: (2025)