Papers
Fast and Differentially Private Fair Clustering
Junyoung Byun, Jaewook Lee
FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract)
Siting Liu, Yuan Pu, Peiyu Liao et al.
Fast-StrucTexT: An Efficient Hourglass Transformer with Modality-guided Dynamic Token Merge for Document Understanding
Mingliang Zhai, Yulin Li, Xiameng Qin et al.
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts
Shubham Sharma, Jette Henderson, Joydeep Ghosh
Feature Staleness Aware Incremental Learning for CTR Prediction
Zhikai Wang, Yanyan Shen, Zibin Zhang et al.
FedBFPT: An Efficient Federated Learning Framework for Bert Further Pre-training
Xin'ao Wang, Huan Li, Ke Chen et al.
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment
Jiahao Liu, Jiang Wu, Jinyu Chen et al.
Federated Graph Semantic and Structural Learning
Wenke Huang, Guancheng Wan, Mang Ye et al.
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation
Weiming Liu, Chaochao Chen, Xinting Liao et al.
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer
Chenghao Liu, Xiaoyang Qu, Jianzong Wang et al.
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks
Xinyu Fu, Irwin King
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity
Nannan Wu, Li Yu, Xuefeng Jiang et al.
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning
Yuanyuan Chen, Zichen Chen, Pengcheng Wu et al.
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation
Hanlin Gu, Jiahuan Luo, Yan Kang et al.
FedSampling: A Better Sampling Strategy for Federated Learning
Tao Qi, Fangzhao Wu, Lingjuan Lyu et al.
Fedstellar: A Platform for Training Models in a Privacy-preserving and Decentralized Fashion
Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Sergio López Bernal et al.
Few-shot Classification via Ensemble Learning with Multi-Order Statistics
Sai Yang, Fan Liu, Delong Chen et al.
FGNet: Towards Filling the Intra-class and Inter-class Gaps for Few-shot Segmentation
Yuxuan Zhang, Wei Yang, Shaowei Wang
Fighting against Organized Fraudsters Using Risk Diffusion-based Parallel Graph Neural Network
Jiacheng Ma, Fan Li, Rui Zhang et al.
Finding an ϵ-Close Minimal Variation of Parameters in Bayesian Networks
Bahare Salmani, Joost-Pieter Katoen
Finding Mixed-Strategy Equilibria of Continuous-Action Games without Gradients Using Randomized Policy Networks
Carlos Martin, Tuomas Sandholm
Find Rhinos without Finding Rhinos: Active Learning with Multimodal Imagery of South African Rhino Habitats
Lucia Gordon, Nikhil Behari, Samuel Collier et al.
Fine-tuned vs. Prompt-tuned Supervised Representations: Which Better Account for Brain Language Representations?
Jingyuan Sun, Marie-Francine Moens
Finite Entailment of UCRPQs over ALC Ontologies (Extended Abstract)
Víctor Gutiérrez-Basulto, Albert Gutowski, Yazmín Ibáñez-García et al.