Papers
Federated Multi-Task Learning under a Mixture of Distributions
Othmane Marfoq, Giovanni Neglia, Aurélien Bellet et al.
Federated Reconstruction: Partially Local Federated Learning
Karan Singhal, Hakim Sidahmed, Zachary Garrett et al.
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis
Sangjoon Park, Gwanghyun Kim, Jeongsol Kim et al.
Few-Round Learning for Federated Learning
Younghyun Park, Dong-Jun Han, Do-Yeon Kim et al.
Few-Shot Data-Driven Algorithms for Low Rank Approximation
Piotr Indyk, Tal Wagner, David Woodruff
Few-Shot Object Detection via Association and DIscrimination
Yuhang Cao, Jiaqi Wang, Ying Jin et al.
Few-Shot Segmentation via Cycle-Consistent Transformer
Gengwei Zhang, Guoliang Kang, Yi Yang et al.
Finding Bipartite Components in Hypergraphs
Peter Macgregor, He Sun
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
Liangbin Xie, Xintao Wang, Chao Dong et al.
Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks
Chen Ma, Xiangyu Guo, Li Chen et al.
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance
Justin Lim, Christina X Ji, Michael Oberst et al.
Fine-grained Generalization Analysis of Inductive Matrix Completion
Antoine Ledent, Rodrigo Alves, Yunwen Lei et al.
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information
Yang Zhang, Ashkan Khakzar, Yawei Li et al.
Fine-Grained Zero-Shot Learning with DNA as Side Information
Sarkhan Badirli, Zeynep Akata, George Mohler et al.
FINE Samples for Learning with Noisy Labels
Taehyeon Kim, Jongwoo Ko, sangwook Cho et al.
Finite Sample Analysis of Average-Reward TD Learning and $Q$-Learning
Sheng Zhang, Zhe Zhang, Siva Theja Maguluri
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai et al.
Fitting summary statistics of neural data with a differentiable spiking network simulator
Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi et al.
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
Ruihan Wu, Chuan Guo, Awni Hannun et al.
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horváth, Stefanos Laskaridis, Mario Almeida et al.
Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
Danruo DENG, Guangyong Chen, Jianye Hao et al.
Flexible Option Learning
Martin Klissarov, Doina Precup
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang, Yidong Wang, Wenxin Hou et al.
FLEX: Unifying Evaluation for Few-Shot NLP
Jonathan Bragg, Arman Cohan, Kyle Lo et al.
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
Emmanuel Bengio, Moksh Jain, Maksym Korablyov et al.