:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Su, Xiaoxin, Zhou, Yipeng, Cui, Laizhong, Guo, Song
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2402.03815
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes
by: Su, Xiaoxin, et al.
Published: (2024)

Mitigating Noise Detriment in Differentially Private Federated Learning with Model Pre-training
by: Jin, Huitong, et al.
Published: (2024)

The Power of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacy
by: Ma, Jiating, et al.
Published: (2024)

On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
by: Guo, Tao, et al.
Published: (2025)

Data-Aware Gradient Compression for FL in Communication-Constrained Mobile Computing
by: Lu, Rongwei, et al.
Published: (2023)

Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
by: Li, Yipeng, et al.
Published: (2024)

Convergence Analysis of Sequential Federated Learning on Heterogeneous Data
by: Li, Yipeng, et al.
Published: (2023)

Ister: Linear Transformer for Efficient Multivariate Time Series Forecasting
by: Cao, Fanpu, et al.
Published: (2024)

FedQV: Leveraging Quadratic Voting in Federated Learning
by: Chu, Tianyue, et al.
Published: (2024)

Federated Learning at the Forefront of Fairness: A Multifaceted Perspective
by: Mukhtiar, Noorain, et al.
Published: (2026)

Automated Discovery of Integral with Deep Learning
by: Yin, Xiaoxin
Published: (2024)

OptiVote: Non-Coherent FSO Over-the-Air Majority Vote for Communication-Efficient Distributed Federated Learning in Space Data Centers
by: Zhang, Anbang, et al.
Published: (2025)

Boosting, Voting Classifiers and Randomized Sample Compression Schemes
by: da Cunha, Arthur, et al.
Published: (2024)

Semantic Voting: Execution-Grounded Consensus for LLM Code Generation
by: Jiang, Shan, et al.
Published: (2026)

Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysis
by: Liang, Yipeng, et al.
Published: (2024)

SignSGD with Federated Voting
by: Park, Chanho, et al.
Published: (2024)

Adversarial Federated Consensus Learning for Surface Defect Classification Under Data Heterogeneity in IIoT
by: Cui, Jixuan, et al.
Published: (2024)

Truncated Rectified Flow Policy for Reinforcement Learning with One-Step Sampling
by: Zhou, Xubin, et al.
Published: (2026)

Dual Consensus: Escaping from Spurious Majority in Unsupervised RLVR via Two-Stage Vote Mechanism
by: Du, Kaixuan, et al.
Published: (2026)

S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
by: Sánchez, Pedro Miguel Sánchez, et al.
Published: (2025)

Efficient Model Compression for Hierarchical Federated Learning
by: Zhu, Xi, et al.
Published: (2024)

Separate Aggregation of Split Network for Personalized Federated Learning
by: Kang, Yunseok, et al.
Published: (2026)

AdaGossip: Adaptive Consensus Step-size for Decentralized Deep Learning with Communication Compression
by: Aketi, Sai Aparna, et al.
Published: (2024)

UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs
by: He, Yufei, et al.
Published: (2024)

Enhancing Security in Federated Learning through Adaptive Consensus-Based Model Update Validation
by: Alsulaimawi, Zahir
Published: (2024)

Sequential Compression Layers for Efficient Federated Learning in Foundational Models
by: Mahla, Navyansh, et al.
Published: (2024)

Federated Learning and Trajectory Compression for Enhanced AIS Coverage
by: Gräupl, Thomas, et al.
Published: (2025)

Enabling Federated Inference via Unsupervised Consensus Embedding
by: Hashimoto, Yui, et al.
Published: (2026)

FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions
by: Ran, Changjuan, et al.
Published: (2024)

Transformer-based Parameter Estimation in Statistics
by: Yin, Xiaoxin, et al.
Published: (2024)

CAFEDistill: Learning Personalized and Dynamic Models through Federated Early-Exit Network Distillation
by: Liu, Boyi, et al.
Published: (2026)

Compressing Model with Few Class-Imbalance Samples: An Out-of-Distribution Expedition
by: Wu, Tian-Shuang, et al.
Published: (2025)

Federated Multi Agent Deep Learning and Neural Networks for Advanced Distributed Sensing in Wireless Networks
by: Muller, Nadine, et al.
Published: (2026)

Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression
by: Zhang, Zhenxiao, et al.
Published: (2024)

Compressed Federated Reinforcement Learning with a Generative Model
by: Beikmohammadi, Ali, et al.
Published: (2024)

Proof-of-Collaborative-Learning: A Multi-winner Federated Learning Consensus Algorithm
by: Sokhankhosh, Amirreza, et al.
Published: (2024)

Shared-Weights Extender and Gradient Voting for Neural Network Expansion
by: Chatzis, Nikolas, et al.
Published: (2025)

Consensus Knowledge Graph Learning via Multi-view Sparse Low Rank Block Model
by: Cai, Tianxi, et al.
Published: (2022)

Rhomboid Tiling for Geometric Graph Deep Learning
by: Zhang, Yipeng, et al.
Published: (2025)

On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee
by: Li, Chenyang, et al.
Published: (2023)