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Federated Learning

1355 directly classified papers

Papers per year

Papers

Causally-Aware Attribute Completion for Incomplete Federated Graph Clustering AAAI 2026

Causality-inspired Federated Learning for Dynamic Spatio-Temporal Graphs AAAI 2026

DA-DFGAS:Differentiable Federated Graph Neural Architecture Search with Distribution-Aware Attentive Aggregation AAAI 2026

Bant: Byzantine Antidote via Trial Function and Trust Scores AAAI 2026

OPTION: An Online Pricing Strategy for Asynchronous Federated Learning Against Free-Riding Attacks AAAI 2026

FedSCAl: Leveraging Server and Client Alignment for Unsupervised Federated Source-Free Domain Adaptation WACV 2026

SD-CSFL: A Synthetic Data-Driven Conformity Scoring Framework for Robust Federated Learning WACV 2026

Personalized Image Privacy Advisors via Federated Daisy-Chaining WACV 2026

Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models WACV 2026

AFL-PRF: Adaptive Federated Learning for Low-Quality Data: Enhancing Performance, Robustness, and Fairness WACV 2026

Federated Model Synchronization for Diagnostic Redefinition through a Novel Selective Parameter Unlearning WACV 2026

FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation EACL 2026

Unlocking Dynamic Inter-Client Spatial Dependencies: A Federated Spatio-temporal Graph Learning Method for Traffic Flow Forecasting AAAI 2026

PAGE: A Unified Approach for Federated Graph Unlearning AAAI 2026

PPFL: A Parameter Behavior-Driven Plug-in Personalization Engine for Federated Learning AAAI 2026

LSHFed: Robust and Communication-Efficient Federated Learning with Locally-Sensitive Hashing Gradient Mapping AAAI 2026

Personalized Federated Learning with Bidirectional Communication Compression via One-Bit Random Sketching AAAI 2026

BIQ: Bisection Interval Quantization for Communication-efficient Federated Learning AAAI 2026

ORVIT: Near-Optimal Online Distributionally Robust Reinforcement Learning AAAI 2026

FedTopo: Topology-Informed Representation Alignment in Federated Learning Under Non-I.I.D. Conditions AAAI 2026

FedLAGC: Towards High Performance System-Heterogeneous Federated Learning via Layer-Adaptive Submodel Extraction and Gradient Correction AAAI 2026

Communication-Efficient Heterogeneous Federated Learning with Sparse Prototypes in Resource-Constrained Environments AAAI 2026

Probabilistic Hash Embeddings for Online Learning of Categorical Features AAAI 2026

FedAU2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training AAAI 2026

Retaliatory Attacks Against Federated Unlearning via Data Leakage AAAI 2026