Papers
Federated Learning with Positive and Unlabeled Data
Xinyang Lin, Hanting Chen, Yixing Xu et al.
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
Pranay Sharma, Rohan Panda, Gauri Joshi et al.
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
Sajad Khodadadian, Pranay Sharma, Gauri Joshi et al.
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting
Tian Zhou, Ziqing Ma, Qingsong Wen et al.
FedNest: Federated Bilevel, Minimax, and Compositional Optimization
Davoud Ataee Tarzanagh, Mingchen Li, Christos Thrampoulidis et al.
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning
Anis Elgabli, Chaouki Ben Issaid, Amrit Singh Bedi et al.
FedNL: Making Newton-Type Methods Applicable to Federated Learning
Mher Safaryan, Rustem Islamov, Xun Qian et al.
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale
Fan Lai, Yinwei Dai, Sanjay Singapuram et al.
Fenrir: Physics-Enhanced Regression for Initial Value Problems
Filip Tronarp, Nathanael Bosch, Philipp Hennig
Fictitious Play and Best-Response Dynamics in Identical Interest and Zero-Sum Stochastic Games
Lucas Baudin, Rida Laraki
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming
Chuan Wen, Jianing Qian, Jierui Lin et al.
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng et al.
Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks
Runpei Dong, Zhanhong Tan, Mengdi Wu et al.
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications
Bokun Wang, Tianbao Yang
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
Andrew J Wagenmaker, Yifang Chen, Max Simchowitz et al.
Fisher SAM: Information Geometry and Sharpness Aware Minimisation
Minyoung Kim, Da Li, Shell X Hu et al.
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
Yuxin Wen, Jonas A. Geiping, Liam Fowl et al.
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Rame, Corentin Dancette, Matthieu Cord
FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers
Abishek Sankararaman, Balakrishnan Narayanaswamy, Vikramank Y Singh et al.
Flashlight: Enabling Innovation in Tools for Machine Learning
Jacob D Kahn, Vineel Pratap, Tatiana Likhomanenko et al.
Flow-based Recurrent Belief State Learning for POMDPs
Xiaoyu Chen, Yao Mark Mu, Ping Luo et al.
Flowformer: Linearizing Transformers with Conservation Flows
Haixu Wu, Jialong Wu, Jiehui Xu et al.
Flow-Guided Sparse Transformer for Video Deblurring
Jing Lin, Yuanhao Cai, Xiaowan Hu et al.
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension
Bruno Loureiro, Cedric Gerbelot, Maria Refinetti et al.
FOCUS: Familiar Objects in Common and Uncommon Settings
Priyatham Kattakinda, Soheil Feizi