Papers
11,015 papers found
Feature Collapse
Thomas Laurent, James von Brecht, Xavier Bresson
Feature emergence via margin maximization: case studies in algebraic tasks
Depen Morwani, Benjamin L. Edelman, Costin-Andrei Oncescu et al.
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation
Haozhao Wang, Haoran Xu, Yichen Li et al.
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
Zilinghan Li, Pranshu Chaturvedi, Shilan He et al.
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
Junyi Li, Feihu Huang, Heng Huang
Federated Causal Discovery from Heterogeneous Data
Loka Li, Ignavier Ng, Gongxu Luo et al.
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin et al.
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
Zhong Zheng, Fengyu Gao, Lingzhou Xue et al.
Federated Recommendation with Additive Personalization
Zhiwei Li, Guodong Long, Tianyi Zhou
Federated Text-driven Prompt Generation for Vision-Language Models
Chen Qiu, Xingyu Li, Chaithanya Kumar Mummadi et al.
Federated Wasserstein Distance
Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
Ziyao Wang, Jianyu Wang, Ang Li
FedImpro: Measuring and Improving Client Update in Federated Learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.
FedInverse: Evaluating Privacy Leakage in Federated Learning
Di Wu, Jun Bai, Yiliao Song et al.
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu et al.
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
Kai Yi, Nidham Gazagnadou, Peter Richtárik et al.
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning
Mingkun Yang, Ran Zhu, Qing Wang et al.
FedWon: Triumphing Multi-domain Federated Learning Without Normalization
Weiming Zhuang, Lingjuan Lyu
Ferret: Refer and Ground Anything Anywhere at Any Granularity
Haoxuan You, Haotian Zhang, Zhe Gan et al.
Few-Shot Detection of Machine-Generated Text using Style Representations
Rafael Alberto Rivera Soto, Kailin Koch, Aleem Khan et al.
Few-shot Hybrid Domain Adaptation of Image Generator
Hengjia Li, Yang Liu, Linxuan Xia et al.
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
Xiaotian Han, Jianfeng Chi, Yu Chen et al.
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
Fiber Monte Carlo
Nick Richardson, Deniz Oktay, Yaniv Ovadia et al.
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text
Nate Gruver, Anuroop Sriram, Andrea Madotto et al.