An Operator Splitting View of Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Malekmohammadi, Saber, Shaloudegi, Kiarash, Hu, Zeou, Yu, Yaoliang |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Semi-Variance Reduction for Fair Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
A Unified Framework for Gradient Aggregation in Multi-Objective Optimization
by: Hu, Zeou, et al.
Published: (2026)
by: Hu, Zeou, et al.
Published: (2026)
Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
LoRA Provides Differential Privacy by Design via Random Sketching
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
Sharpness-Aware Parameter Selection for Machine Unlearning
by: Malekmohammadi, Saber, et al.
Published: (2025)
by: Malekmohammadi, Saber, et al.
Published: (2025)
One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently
by: Li, Weida, et al.
Published: (2024)
by: Li, Weida, et al.
Published: (2024)
The Representation-Rationalizability Tradeoff in Reward Learning
by: Dong, Jing, et al.
Published: (2026)
by: Dong, Jing, et al.
Published: (2026)
Stochastic Forward-Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets
by: Lu, Haoye, et al.
Published: (2025)
by: Lu, Haoye, et al.
Published: (2025)
Efficient Bilevel Optimization with KFAC-Based Hypergradients
by: Liao, Disen, et al.
Published: (2026)
by: Liao, Disen, et al.
Published: (2026)
SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples
by: Lu, Haoye, et al.
Published: (2025)
by: Lu, Haoye, et al.
Published: (2025)
SFBD-OMNI: Bridge models for lossy measurement restoration with limited clean samples
by: Lu, Haoye, et al.
Published: (2025)
by: Lu, Haoye, et al.
Published: (2025)
Adaptive Context Length Optimization with Low-Frequency Truncation for Multi-Agent Reinforcement Learning
by: Duan, Wenchang, et al.
Published: (2025)
by: Duan, Wenchang, et al.
Published: (2025)
$f$-MICL: Understanding and Generalizing InfoNCE-based Contrastive Learning
by: Lu, Yiwei, et al.
Published: (2024)
by: Lu, Yiwei, et al.
Published: (2024)
Indiscriminate Data Poisoning Attacks on Neural Networks
by: Lu, Yiwei, et al.
Published: (2022)
by: Lu, Yiwei, et al.
Published: (2022)
Order Optimal Bounds for One-Shot Federated Learning over non-Convex Loss Functions
by: Sharifnassab, Arsalan, et al.
Published: (2021)
by: Sharifnassab, Arsalan, et al.
Published: (2021)
TreeGrad-Ranker: Feature Ranking via $O(L)$-Time Gradients for Decision Trees
by: Li, Weida, et al.
Published: (2026)
by: Li, Weida, et al.
Published: (2026)
Provably Adaptive Linear Approximation for the Shapley Value and Beyond
by: Li, Weida, et al.
Published: (2026)
by: Li, Weida, et al.
Published: (2026)
SplitFedZip: Learned Compression for Data Transfer Reduction in Split-Federated Learning
by: Shiranthika, Chamani, et al.
Published: (2024)
by: Shiranthika, Chamani, et al.
Published: (2024)
A Generalized Meta Federated Learning Framework with Theoretical Convergence Guarantees
by: Jamali, Mohammad Vahid, et al.
Published: (2025)
by: Jamali, Mohammad Vahid, et al.
Published: (2025)
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games
by: Dong, Jing, et al.
Published: (2024)
by: Dong, Jing, et al.
Published: (2024)
Structure Preserving Diffusion Models
by: Lu, Haoye, et al.
Published: (2024)
by: Lu, Haoye, et al.
Published: (2024)
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
by: Lu, Yiwei, et al.
Published: (2024)
by: Lu, Yiwei, et al.
Published: (2024)
Separate Aggregation of Split Network for Personalized Federated Learning
by: Kang, Yunseok, et al.
Published: (2026)
by: Kang, Yunseok, et al.
Published: (2026)
Data Heterogeneity and Forgotten Labels in Split Federated Learning
by: Tirana, Joana, et al.
Published: (2025)
by: Tirana, Joana, et al.
Published: (2025)
SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning
by: Shan, Yimeng, et al.
Published: (2026)
by: Shan, Yimeng, et al.
Published: (2026)
A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
by: Jin, Ruinan, et al.
Published: (2024)
by: Jin, Ruinan, et al.
Published: (2024)
Towards Privacy-Preserving and Heterogeneity-aware Split Federated Learning via Probabilistic Masking
by: Wang, Xingchen, et al.
Published: (2025)
by: Wang, Xingchen, et al.
Published: (2025)
Learning Neural Differential Algebraic Equations via Operator Splitting
by: Koch, James, et al.
Published: (2024)
by: Koch, James, et al.
Published: (2024)
DiffBreak: Is Diffusion-Based Purification Robust?
by: Kassis, Andre, et al.
Published: (2024)
by: Kassis, Andre, et al.
Published: (2024)
Semantic Communication-Enhanced Split Federated Learning for Vehicular Networks: Architecture, Challenges, and Case Study
by: Yu, Lu, et al.
Published: (2026)
by: Yu, Lu, et al.
Published: (2026)
ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning
by: Meng, Chuiyang, et al.
Published: (2026)
by: Meng, Chuiyang, et al.
Published: (2026)
MUC: Machine Unlearning for Contrastive Learning with Black-box Evaluation
by: Wang, Yihan, et al.
Published: (2024)
by: Wang, Yihan, et al.
Published: (2024)
KoReA-SFL: Knowledge Replay-based Split Federated Learning Against Catastrophic Forgetting
by: Xia, Zeke, et al.
Published: (2024)
by: Xia, Zeke, et al.
Published: (2024)
BridgePure: Limited Protection Leakage Can Break Black-Box Data Protection
by: Wang, Yihan, et al.
Published: (2024)
by: Wang, Yihan, et al.
Published: (2024)
Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing
by: Qiang, Xianke, et al.
Published: (2024)
by: Qiang, Xianke, et al.
Published: (2024)
HealSplit: Towards Self-Healing through Adversarial Distillation in Split Federated Learning
by: Xie, Yuhan, et al.
Published: (2025)
by: Xie, Yuhan, et al.
Published: (2025)
Distributed Detection of Adversarial Attacks in Multi-Agent Reinforcement Learning with Continuous Action Space
by: Kazari, Kiarash, et al.
Published: (2025)
by: Kazari, Kiarash, et al.
Published: (2025)
Efficient Split Federated Learning for Large Language Models over Communication Networks
by: Zhao, Kai, et al.
Published: (2025)
by: Zhao, Kai, et al.
Published: (2025)
Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming
by: King, Ethan, et al.
Published: (2024)
by: King, Ethan, et al.
Published: (2024)
Similar Items
-
Semi-Variance Reduction for Fair Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024) -
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024) -
A Unified Framework for Gradient Aggregation in Multi-Objective Optimization
by: Hu, Zeou, et al.
Published: (2026) -
Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024) -
LoRA Provides Differential Privacy by Design via Random Sketching
by: Malekmohammadi, Saber, et al.
Published: (2024)