Awesome Optimization

Key papers

• Better Generative Replay for Continual Federated Learning (2023)
  Daiqing Qi et al.
  8.60
• FederBoost: Private Federated Learning for GBDT (2020)
  Zhihua Tian et al.
  8.19
• Federated Domain Generalization: A Survey (2023)
  Ying Li et al.
  7.59
• Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data (2021)
  Zilong Zhao et al.
  7.50
• FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models (2025)
  Hui Lin et al.
  7.44
• Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation (2023)
  Francesco Santini et al.
  7.01
• Knowledge Distillation for Federated Learning: a Practical Guide (2022)
  Alessio Mora et al.
  6.78
• On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach (2026)
  Jiahui Bai et al.
  6.72
• Personalized Semi-Supervised Federated Learning for Human Activity Recognition (2021)
  Riccardo Presotto et al.
  6.53
• Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy (2026)
  Emre Ardıç et al.
  6.52
• Fair and efficient contribution valuation for vertical federated learning (2022)
  Zhenan Fan et al.
  6.39
• Advancing MRI Reconstruction: A Systematic Review of Deep Learning and Compressed Sensing Integration (2025)
  Mojtaba Safari et al.
  6.12
• Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case (2025)
  William Marfo et al.
  6.12
• LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data (2025)
  Yuxin Zhang et al.
  5.84
• AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks (2024)
  Zheng Lin et al.
  5.80
• Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? (2021)
  Shuxiao Chen et al.
  5.72
• Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems (2025)
  William Marfo et al.
  5.54
• Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis (2024)
  Guangchen Lan et al.
  5.34
• One-Shot Federated Learning with Classifier-Free Diffusion Models (2025)
  Obaidullah Zaland et al.
  5.24
• FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning (2025)
  Yanbing Zhou et al.
  5.18
• UAV-Assisted Multi-Task Federated Learning with Task Knowledge Sharing (2025)
  Yubo Yang et al.
  5.18
• Federated Learning with Sample-level Client Drift Mitigation (2025)
  Haoran Xu et al.
  5.18
• Unlearning Clients, Features and Samples in Vertical Federated Learning (2025)
  Ayush K. Varshney et al.
  5.18
• Local Differential Privacy with Correlated Noise Achieves Central-DP Optimal Cost (2026)
  Madhura Pathegama et al.
  4.95
• A Tight Theory of Error Feedback Algorithms in Distributed Optimization (2026)
  Daniel Berg Thomsen et al.
  4.95
• PM-MOE: Mixture of Experts on Private Model Parameters for Personalized Federated Learning (2025)
  Yu Feng et al.
  4.82
• A Two-Stage CAE-Based Federated Learning Framework for Efficient Jamming Detection in 5G Networks (2025)
  Samhita Kuili et al.
  4.76
• Decentralized Low-Rank Fine-Tuning of Large Language Models (2025)
  Sajjad Ghiasvand et al.
  4.76
• Federated Large Language Models: Current Progress and Future Directions (2024)
  Yuhang Yao et al.
  4.54
• Elastic Federated Learning over Open Radio Access Network (O-RAN) for Concurrent Execution of Multiple Distributed Learning Tasks (2023)
  Payam Abdisarabshali et al.
  4.52
• Federated Multi-Armed Bandits Under Byzantine Attacks (2022)
  Artun Saday et al.
  4.48
• QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning (2026)
  Nazmus Shakib Shadin et al.
  4.39
• FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching (2026)
  Haoran Zhang et al.
  4.39
• Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning (2026)
  Haengbok Chung et al.
  4.39
• Inverse Probability Weighting and Age-of-Information Aggregation for Decentralized Federated Learning under Partial Reception (2026)
  Chanuka A. S. Hewa Kaluannakkage et al.
  4.39
• Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT (2025)
  Xiaohong Yang et al.
  4.36
• Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping (2023)
  Martin Pelikan et al.
  4.35
• FIRMA: FIbonacci Ring Model Aggregation for Privacy-preserving Federated Learning (2026)
  Rachid Hedjam
  4.33
• Semantic-aware Token Selection and Resource Optimization for Communication-efficient Split Federated Fine-tuning in Edge Intelligence (2026)
  Xianke Qiang et al.
  4.33
• Provably Communication-Efficient and Privacy-Preserving Federated Graph Neural Networks (2026)
  Zhishuai Guo et al.
  4.33
• Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System (2026)
  Cheng-Wei Ching et al.
  4.33
• Separate Aggregation of Split Network for Personalized Federated Learning (2026)
  Yunseok Kang et al.
  4.33
• Image Feature Fusion-based Federated Client Unlearning (FCU) (2026)
  Hangyi Shen et al.
  4.33
• Autonomic Federated-Market Orchestration for the Edge-Cloud Continuum (2026)
  Lauri Lov\'en et al.
  4.33
• Bandwidth Allocation with Device Partitioning for Federated Learning over Industrial IoT networks (2026)
  Kangmin Kim et al.
  4.33
• DG-CoLearn: An Efficient Collaborative Learning Framework for Dynamic Graphs (2026)
  Ashley Hoi-Ting Au et al.
  4.33
• Efficient Deployment of Large Language Models on Resource-constrained Devices (2025)
  Zhiwei Yao et al.
  4.25
• Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation (2025)
  Xiaoxiao He et al.
  4.25
• Cognitive Edge Computing: A Comprehensive Survey on Optimizing Large Models and AI Agents for Pervasive Deployment (2025)
  Xubin Wang et al.
  4.25
• Over-the-Air Fair Federated Learning via Multi-Objective Optimization (2025)
  Shayan Mohajer Hamidi et al.
  4.25
• Personalized Federated Learning for Cellular VR: Online Learning and Dynamic Caching (2025)
  Krishnendu S. Tharakan et al.
  4.25
• A Selective Homomorphic Encryption Approach for Faster Privacy-Preserving Federated Learning (2025)
  Abdulkadir Korkmaz and Praveen Rao
  4.25
• Certifying the Right to Be Forgotten: Primal-Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning (2025)
  Yu Jiang et al.
  4.20
• Hierarchical Split Federated Learning: Convergence Analysis and System Optimization (2024)
  Zheng Lin et al.
  4.19
• Distributed Saddle-Point Problems: Lower Bounds, Near-Optimal and Robust Algorithms (2020)
  Aleksandr Beznosikov et al.
  4.13
• Distributed Adaptive Learning Under Communication Constraints (2021)
  Marco Carpentiero et al.
  4.13
• Entropy-driven Fair and Effective Federated Learning (2023)
  Lin Wang et al.
  4.13
• Federated Learning for Heterogeneous Electronic Health Record Systems with Cost Effective Participant Selection (2024)
  Jiyoun Kim et al.
  4.13
• Floe: Federated Specialization for Real-Time LLM-SLM Inference (2026)
  Chunlin Tian et al.
  4.04
• Towards Privacy-Preserving Mental Health Support with Large Language Models (2026)
  Dong Xue et al.
  3.98