Cover Image

FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jiang, Zhonghua, Xu, Jimin, Zhang, Shengyu, Shen, Tao, Li, Jiwei, Kuang, Kun, Cai, Haibin, Wu, Fei
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Simpson's Paradox in Behavioral Curves: How Aggregation Distorts Parametric Models of User Dynamics
by: Zhou, Chao
Published: (2026)

ModelGPT: Unleashing LLM's Capabilities for Tailored Model Generation
by: Tang, Zihao, et al.
Published: (2024)

Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems
by: Zhang, Shengyu, et al.
Published: (2024)

FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
by: Liu, Xiang, et al.
Published: (2023)

MergeNet: Knowledge Migration across Heterogeneous Models, Tasks, and Modalities
by: Li, Kunxi, et al.
Published: (2024)

FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning
by: Shen, Tao, et al.
Published: (2025)

Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation
by: Lv, Zheqi, et al.
Published: (2025)

FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
by: Li, Yunbo, et al.
Published: (2025)

FedPID: An Aggregation Method for Federated Learning
by: Mächler, Leon, et al.
Published: (2024)

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
by: Wu, Anpeng, et al.
Published: (2024)

Simpson's Paradox with Any Given Number of Factors
by: Dai, Guisheng, et al.
Published: (2025)

Simpson's Paradox and the Accuracy-Fluency Tradeoff in Translation
by: Lim, Zheng Wei, et al.
Published: (2024)

FedAH: Aggregated Head for Personalized Federated Learning
by: Zhou, Pengzhan, et al.
Published: (2024)

FedAgg: Adaptive Federated Learning with Aggregated Gradients
by: Yuan, Wenhao, et al.
Published: (2023)

FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation
by: Lin, Li, et al.
Published: (2024)

FedADP: Unified Model Aggregation for Federated Learning with Heterogeneous Model Architectures
by: Wang, Jiacheng, et al.
Published: (2025)

FedGuCci: Making Local Models More Connected in Landscape for Federated Learning
by: Li, Zexi, et al.
Published: (2024)

pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning
by: Lai, Jiahao, et al.
Published: (2024)

FedBaF: Federated Learning Aggregation Biased by a Foundation Model
by: Park, Jong-Ik, et al.
Published: (2024)

FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning
by: Devkota, Alina, et al.
Published: (2026)

FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning
by: Fan, Boyu, et al.
Published: (2024)

Poster: FedBlockParadox -- A Framework for Simulating and Securing Decentralized Federated Learning
by: Digregorio, Gabriele, et al.
Published: (2025)

Log-Likelihood, Simpson's Paradox, and the Detection of Machine-Generated Text
by: Kempton, Tom, et al.
Published: (2026)

Finding Non-Redundant Simpson's Paradox from Multidimensional Data
by: Yang, Yi, et al.
Published: (2025)

FedSKD: Aggregation-free Model-heterogeneous Federated Learning via Multi-dimensional Similarity Knowledge Distillation for Medical Image Classification
by: Weng, Ziqiao, et al.
Published: (2025)

FedCross: Towards Accurate Federated Learning via Multi-Model Cross-Aggregation
by: Hu, Ming, et al.
Published: (2022)

MadaKV: Adaptive Modality-Perception KV Cache Eviction for Efficient Multimodal Long-Context Inference
by: Li, Kunxi, et al.
Published: (2025)

FedCAP: Robust Federated Learning via Customized Aggregation and Personalization
by: Li, Youpeng, et al.
Published: (2024)

FedIA: Towards Domain-Robust Aggregation in Federated Graph Learning
by: Zhou, Zhanting, et al.
Published: (2025)

FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation
by: Xhemrishi, Marvin, et al.
Published: (2023)

FedEGG: Federated Learning with Explicit Global Guidance
by: Zhai, Kun, et al.
Published: (2024)

FedAPT: Federated Adversarial Prompt Tuning for Vision-Language Models
by: Zhai, Kun, et al.
Published: (2025)

Reasoning Models Ace the CFA Exams
by: Patel, Jaisal, et al.
Published: (2025)

GaussianTalker: Speaker-specific Talking Head Synthesis via 3D Gaussian Splatting
by: Yu, Hongyun, et al.
Published: (2024)

Counterfactual Slopes and Their Applications in Social Stratification
by: Yu, Ang, et al.
Published: (2024)

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
by: Yi, Liping, et al.
Published: (2023)

A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
by: Sun, Yan, et al.
Published: (2024)

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning
by: Haque, Md Rafid, et al.
Published: (2025)

FedIN: Federated Intermediate Layers Learning for Model Heterogeneity
by: Chan, Yun-Hin, et al.
Published: (2023)

Watching the FedWatch
by: Stefano Bonini, et al.
Published: (2025)