Papers
Feature-Preserving Mesh Decimation for Normal Integration
Moritz Heep, Sven Behnke, Eduard Zell
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse
Seung Hyun Cheon, Anneke Wernerfelt, Sorelle Friedler et al.
Feature Selection for Latent Factor Models
Rittwika Kansabanik, Adrian Barbu
Feature Space Perturbation: A Panacea to Enhanced Transferability Estimation
Prafful Kumar Khoba, Zijian Wang, Chetan Arora et al.
Feature Spectrum Learning for Remote Sensing Change Detection
Qi Zang, Dong Zhao, Shuang Wang et al.
Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning
Jeffrey Olmo, Jared Wilson, Max Forsey et al.
Feature-Structure Adaptive Completion Graph Neural Network for Cold-start Recommendation
Songyuan Lei, Xinglong Chang, Zhizhi Yu et al.
FEAT-writing: An Interactive Training System for Argumentative Writing
Yuning Ding, Franziska Wehrhahn, Andrea Horbach
FE-CLIP: Frequency Enhanced CLIP Model for Zero-Shot Anomaly Detection and Segmentation
Tao Gong, Qi Chu, Bin Liu et al.
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning
Jialuo He, Wei Chen, Xiaojin Zhang
FedAGC: Federated Continual Learning with Asymmetric Gradient Correction
Chengchao Zhang, Fanhua Shang, Hongying Liu et al.
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data
Yuxia Sun, Aoxiang Sun, Siyi Pan et al.
FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors
Changlong Shi, He Zhao, Bingjie Zhang et al.
FedBG: Proactively Mitigating Bias in Cross-Domain Graph Federated Learning Using Background Data
Sheng Huang, Lele Fu, Tianchi Liao et al.
FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models
Haokun Chen, Hang Li, Yao Zhang et al.
FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning
Hao Zheng, Zhigang Hu, Liu Yang et al.
FedCCH: Automatic Personalized Graph Federated Learning for Inter-Client and Intra-Client Heterogeneity
Pengfei Jiao, Zian Zhou, Meiting Xue et al.
FedCFA: Alleviating Simpson’s Paradox in Model Aggregation with Counterfactual Federated Learning
Zhonghua Jiang, Jimin Xu, Shengyu Zhang et al.
FedCM: Client Clustering and Migration in Federated Learning via Gradient Path Similarity and Update Direction Deviation
Peng Wang, Shoupeng Lu, Hao Yin et al.
FedCoT: Federated Chain-of-Thought Distillation for Large Language Models
Tao Fan, Weijing Chen, Yan Kang et al.
FedCPD:Personalized Federated Learning with Prototype-Enhanced Representation and Memory Distillation
Kaili Jin, Li Xu, Xiaoding Wang et al.
FedCross: Intertemporal Federated Learning Under Evolutionary Games
Jianfeng Lu, Ying Zhang, Riheng Jia et al.
FedCS: Coreset Selection for Federated Learning
Chenhe Hao, Weiying Xie, Daixun Li et al.
FedCSR: A Federated Framework for Multi-Platform Cross-Domain Sequential Recommendation with Dual Contrastive Learning
Dongyi Zheng, Hongyu Zhang, Jianyang Zhai et al.
Fed-DFA: Federated Distillation for Heterogeneous Model Fusion Through the Adversarial Lens
Zichen Wang, Feng Yan, Tianyi Wang et al.