Federated Learning with Reduced Information Leakage and Computation
Fuente:
arXiv
Saved in:
| Main Authors: | Yin, Tongxin, Tan, Xuwei, Zhang, Xueru, Khalili, Mohammad Mahdi, Liu, Mingyan |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Lookahead Counterfactual Fairness
by: Zuo, Zhiqun, et al.
Published: (2024)
by: Zuo, Zhiqun, et al.
Published: (2024)
Demographic-Agnostic Fairness without Harm
by: Cai, Zhongteng, et al.
Published: (2025)
by: Cai, Zhongteng, et al.
Published: (2025)
DroughtSet: Understanding Drought Through Spatial-Temporal Learning
by: Tan, Xuwei, et al.
Published: (2024)
by: Tan, Xuwei, et al.
Published: (2024)
ProFL: Performative Robust Optimal Federated Learning
by: Zheng, Xue, et al.
Published: (2024)
by: Zheng, Xue, et al.
Published: (2024)
Providing Differential Privacy for Federated Learning Over Wireless: A Cross-layer Framework
by: Mao, Jiayu, et al.
Published: (2024)
by: Mao, Jiayu, et al.
Published: (2024)
Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection
by: Tan, Xuwei, et al.
Published: (2025)
by: Tan, Xuwei, et al.
Published: (2025)
Benchmarking Bias Mitigation Toward Fairness Without Harm from Vision to LVLMs
by: Tan, Xuwei, et al.
Published: (2026)
by: Tan, Xuwei, et al.
Published: (2026)
SPRINT: Stochastic Performative Prediction With Variance Reduction
by: Xie, Tian, et al.
Published: (2025)
by: Xie, Tian, et al.
Published: (2025)
Long-Term Fairness with Unknown Dynamics
by: Yin, Tongxin, et al.
Published: (2023)
by: Yin, Tongxin, et al.
Published: (2023)
Achieving Fairness Without Harm via Selective Demographic Experts
by: Tan, Xuwei, et al.
Published: (2025)
by: Tan, Xuwei, et al.
Published: (2025)
Individual Fairness In Strategic Classification
by: Zuo, Zhiqun, et al.
Published: (2026)
by: Zuo, Zhiqun, et al.
Published: (2026)
Data Poisoning and Leakage Analysis in Federated Learning
by: Wei, Wenqi, et al.
Published: (2024)
by: Wei, Wenqi, et al.
Published: (2024)
Post-processing for Fair Regression via Explainable SVD
by: Zuo, Zhiqun, et al.
Published: (2025)
by: Zuo, Zhiqun, et al.
Published: (2025)
An Efficient Training Algorithm for Models with Block-wise Sparsity
by: Zhu, Ding, et al.
Published: (2025)
by: Zhu, Ding, et al.
Published: (2025)
AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features
by: Zhu, Xudong, et al.
Published: (2025)
by: Zhu, Xudong, et al.
Published: (2025)
ECG Signal Denoising Using Multi-scale Patch Embedding and Transformers
by: Zhu, Ding, et al.
Published: (2024)
by: Zhu, Ding, et al.
Published: (2024)
Neuroplasticity and Corruption in Model Mechanisms: A Case Study Of Indirect Object Identification
by: Chhabra, Vishnu Kabir, et al.
Published: (2025)
by: Chhabra, Vishnu Kabir, et al.
Published: (2025)
On the transferability of Sparse Autoencoders for interpreting compressed models
by: Gupte, Suchit, et al.
Published: (2025)
by: Gupte, Suchit, et al.
Published: (2025)
Convergence Analysis for Learning Orthonormal Deep Linear Neural Networks
by: Qin, Zhen, et al.
Published: (2023)
by: Qin, Zhen, et al.
Published: (2023)
Non-linear Welfare-Aware Strategic Learning
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing
by: Fang, Minghong, et al.
Published: (2025)
by: Fang, Minghong, et al.
Published: (2025)
Privacy-Aware Randomized Quantization via Linear Programming
by: Cai, Zhongteng, et al.
Published: (2024)
by: Cai, Zhongteng, et al.
Published: (2024)
Location Leakage in Federated Signal Maps
by: Bakopoulou, Evita, et al.
Published: (2021)
by: Bakopoulou, Evita, et al.
Published: (2021)
Self-Consuming Generative Models with Adversarially Curated Data
by: Wei, Xiukun, et al.
Published: (2025)
by: Wei, Xiukun, et al.
Published: (2025)
PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA
by: Wang, Shihao, et al.
Published: (2026)
by: Wang, Shihao, et al.
Published: (2026)
From Emergence to Control: Probing and Modulating Self-Reflection in Language Models
by: Zhu, Xudong, et al.
Published: (2025)
by: Zhu, Xudong, et al.
Published: (2025)
Learning to Detect Critical Nodes in Sparse Graphs via Feature Importance Awareness
by: Tan, Xuwei, et al.
Published: (2021)
by: Tan, Xuwei, et al.
Published: (2021)
Learning under Imitative Strategic Behavior with Unforeseeable Outcomes
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
GraphDLG: Exploring Deep Leakage from Gradients in Federated Graph Learning
by: Wei, Shuyue, et al.
Published: (2026)
by: Wei, Shuyue, et al.
Published: (2026)
Gradients Stand-in for Defending Deep Leakage in Federated Learning
by: Yi, H., et al.
Published: (2024)
by: Yi, H., et al.
Published: (2024)
Building Gradient Bridges: Label Leakage from Restricted Gradient Sharing in Federated Learning
by: Zhang, Rui, et al.
Published: (2024)
by: Zhang, Rui, et al.
Published: (2024)
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
by: Papageorgiou, Yiannis, et al.
Published: (2026)
by: Papageorgiou, Yiannis, et al.
Published: (2026)
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning
by: Fan, Mingyuan, et al.
Published: (2022)
by: Fan, Mingyuan, et al.
Published: (2022)
Understanding the Role of Layer Normalization in Label-Skewed Federated Learning
by: Zhang, Guojun, et al.
Published: (2023)
by: Zhang, Guojun, et al.
Published: (2023)
A Unified Virtual Mixture-of-Experts Framework:Enhanced Inference and Hallucination Mitigation in Single-Model System
by: Liu, Mingyan
Published: (2025)
by: Liu, Mingyan
Published: (2025)
Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm
by: Pham, Thai-Hoang, et al.
Published: (2024)
by: Pham, Thai-Hoang, et al.
Published: (2024)
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
by: Shao, Jiawei, et al.
Published: (2023)
by: Shao, Jiawei, et al.
Published: (2023)
Stabilizing Self-Consuming Diffusion Models with Latent Space Filtering
by: Cai, Zhongteng, et al.
Published: (2025)
by: Cai, Zhongteng, et al.
Published: (2025)
Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning
by: Kim, Joon, et al.
Published: (2024)
by: Kim, Joon, et al.
Published: (2024)
Similar Items
-
Lookahead Counterfactual Fairness
by: Zuo, Zhiqun, et al.
Published: (2024) -
Demographic-Agnostic Fairness without Harm
by: Cai, Zhongteng, et al.
Published: (2025) -
DroughtSet: Understanding Drought Through Spatial-Temporal Learning
by: Tan, Xuwei, et al.
Published: (2024) -
ProFL: Performative Robust Optimal Federated Learning
by: Zheng, Xue, et al.
Published: (2024) -
Providing Differential Privacy for Federated Learning Over Wireless: A Cross-layer Framework
by: Mao, Jiayu, et al.
Published: (2024)