Papers
Feature Directions Matter: Long-Tailed Learning via Rotated Balanced Representation
Gao Peifeng, Qianqian Xu, Peisong Wen et al.
Feature Expansion for Graph Neural Networks
Jiaqi Sun, Lin Zhang, Guangyi Chen et al.
Feature learning in deep classifiers through Intermediate Neural Collapse
Akshay Rangamani, Marius Lindegaard, Tomer Galanti et al.
Feature Programming for Multivariate Time Series Prediction
Alex Daniel Reneau, Jerry Yao-Chieh Hu, Ammar Gilani et al.
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks
Bingqing Song, Prashant Khanduri, Xinwei Zhang et al.
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction
Yongxin Guo, Xiaoying Tang, Tao Lin
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction
Jianyi Zhang, Ang Li, Minxue Tang et al.
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization
Hao Zhang, Chenglin Li, Wenrui Dai et al.
FedDisco: Federated Learning with Discrepancy-Aware Collaboration
Rui Ye, Mingkai Xu, Jianyu Wang et al.
Federated Adversarial Learning: A Framework with Convergence Analysis
Xiaoxiao Li, Zhao Song, Jiaming Yang
Federated Conformal Predictors for Distributed Uncertainty Quantification
Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy et al.
Federated Heavy Hitter Recovery under Linear Sketching
Adria Gascon, Peter Kairouz, Ziteng Sun et al.
Federated Linear Contextual Bandits with User-level Differential Privacy
Ruiquan Huang, Huanyu Zhang, Luca Melis et al.
Federated Online and Bandit Convex Optimization
Kumar Kshitij Patel, Lingxiao Wang, Aadirupa Saha et al.
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization
Zhen Wang, Weirui Kuang, Ce Zhang et al.
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models
Songze Li, Duanyi Yao, Jin Liu
FeDXL: Provable Federated Learning for Deep X-Risk Optimization
Zhishuai Guo, Rong Jin, Jiebo Luo et al.
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
Haoyue Bai, Gregory Canal, Xuefeng Du et al.
Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
Georgii Sergeevich Novikov, Daniel Bershatsky, Julia Gusak et al.
Few-Sample Feature Selection via Feature Manifold Learning
David Cohen, Tal Shnitzer, Yuval Kluger et al.
Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
Yeonsung Jung, Hajin Shim, June Yong Yang et al.
Finding Generalization Measures by Contrasting Signal and Noise
Jiaye Teng, Bohang Zhang, Ruichen Li et al.
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
Yizhen Zheng, He Zhang, Vincent Lee et al.
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron
Jingfeng Wu, Difan Zou, Zixiang Chen et al.
Fisher Information Embedding for Node and Graph Learning
Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt