Papers
11,015 papers found
Fair Attribute Completion on Graph with Missing Attributes
Dongliang Guo, Zhixuan Chu, Sheng Li
FaiREE: fair classification with finite-sample and distribution-free guarantee
Puheng Li, James Zou, Linjun Zhang
FairGBM: Gradient Boosting with Fairness Constraints
André Cruz, Catarina G Belém, João Bravo et al.
Fairness and Accuracy under Domain Generalization
Thai-Hoang Pham, Xueru Zhang, Ping Zhang
Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes
Fengda Zhang, Kun Kuang, Long Chen et al.
Fake It Until You Make It : Towards Accurate Near-Distribution Novelty Detection
Hossein Mirzaei, Mohammadreza Salehi, Sajjad Shahabi et al.
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
Yihao Feng, Shentao Yang, Shujian Zhang et al.
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
Michał Zawalski, Michał Tyrolski, Konrad Czechowski et al.
Faster federated optimization under second-order similarity
Ahmed Khaled, Chi Jin
Faster Gradient-Free Methods for Escaping Saddle Points
Hualin Zhang, Bin Gu
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
Shicong Cen, Yuejie Chi, Simon Shaolei Du et al.
FastFill: Efficient Compatible Model Update
Florian Jaeckle, Fartash Faghri, Ali Farhadi et al.
Fast Nonlinear Vector Quantile Regression
Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano et al.
Fast Sampling of Diffusion Models with Exponential Integrator
Qinsheng Zhang, Yongxin Chen
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang et al.
Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks
Sravanti Addepalli, Anshul Nasery, Venkatesh Babu Radhakrishnan et al.
FedDAR: Federated Domain-Aware Representation Learning
Aoxiao Zhong, Hao He, Zhaolin Ren et al.
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
Han Guo, Philip Greengard, Hongyi Wang et al.
Federated Learning from Small Datasets
Michael Kamp, Jonas Fischer, Jilles Vreeken
Federated Nearest Neighbor Machine Translation
Yichao Du, Zhirui Zhang, Bingzhe Wu et al.
Federated Neural Bandits
Zhongxiang Dai, Yao Shu, Arun Verma et al.
FedExP: Speeding Up Federated Averaging via Extrapolation
Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi
FedFA: Federated Feature Augmentation
Tianfei Zhou, Ender Konukoglu
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy
Yan Sun, Li Shen, Tiansheng Huang et al.