Poster Papers
24,624 papers found • Page 101 of 493
Conference
Federated Granger Causality Learning For Interdependent Clients With State Space Representation
Ayush Mohanty, Nazal Mohamed, Paritosh Ramanan et al.
Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance
Guoqing Chao, Zhenghao Zhang, Lei Meng et al.
Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
Ruhan Wang, Zhiyong Wang, Chengkai Huang et al.
Federated Learning for Feature Generalization with Convex Constraints
Dongwon Kim, Donghee Kim, Sung Kuk Shyn et al.
Federated Learning with Domain Shift Eraser
Zheng Wang, Zihui Wang, Zheng Wang et al.
Federated Multi-armed Bandits with Efficient Bit-Level Communications
Haoran Zhang, Yang Xu, Xuchuang Wang et al.
Federated Node-Level Clustering Network with Cross-Subgraph Link Mending
Jingxin Liu, Renda Han, Wenxuan Tu et al.
Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework
Guan Huang, Tao Shu
Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data
Hang Phung, Manh Nguyen, Thanh Huynh et al.
Federated Representation Angle Learning
Liping Yi, Han Yu, Gang Wang et al.
Federated Residual Low-Rank Adaption of Large Language Models
Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.
FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
Li Zhang, Zhongxuan Han, XiaoHua Feng et al.
FedFree: Breaking Knowledge-sharing Barriers through Layer-wise Alignment in Heterogeneous Federated Learning
Haizhou Du, Yiran Xiang, Yiwen Cai et al.
FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Chenxin Li et al.
FedIGL: Federated Invariant Graph Learning for Non-IID Graphs
Lingren Wang, Wenxuan Tu, Jiaxin Wang et al.
FedLPA: Local Prior Alignment for Heterogeneous Federated Generalized Category Discovery
Geeho Kim, Jinu Lee, Bohyung Han
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
Changlong Shi, Jinmeng Li, He Zhao et al.
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
Junhyeog Yun, Minui Hong, Gunhee Kim
FedMGP: Personalized Federated Learning with Multi-Group Text-Visual Prompts
Weihao Bo, Yanpeng Sun, Yu Wang et al.
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
Gongxi Zhu, Donghao Li, Hanlin Gu et al.
FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
Mainak Singha, Subhankar Roy, Sarthak Mehrotra et al.
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning
Ganyu Wang, Jinjie Fang, Maxwell (Juncheng) Yin et al.
FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift
yong zhang, Feng Liang, Guanghu Yuan et al.
FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation
Chengying Fang, Wenke Huang, Guancheng Wan et al.
FED-PsyAU: Privacy-Preserving Micro-Expression Recognition via Psychological AU Coordination and Dynamic Facial Motion Modeling
Jingting Li, Yu Qian, Lin Zhao et al.
FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
Yunbo Li, Jiaping Gui, Zhihang Deng et al.
FedRACE: A Hierarchical and Statistical Framework for Robust Federated Learning
Gang Yan, Sikai Yang, Wan Du
FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
Fan Wu, Xinyu Yan, Jiabei Liu et al.
FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling
Hong Huang, Jinhai Yang, Yuan Chen et al.
FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
Pukang Ye, Luo Junwei, Jiachen Shen et al.
FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning through Symbolic Model Updates
Xinyi Lu, Hao Zhang, Chenglin Li et al.
FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity
Zihan Tan, Guancheng Wan, Wenke Huang et al.
FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
Seanie Lee, Sangwoo Park, Dong Bok Lee et al.
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Shannon How, Jagmohan Chauhan, Geoff Merrett et al.
FedVLA: Federated Vision-Language-Action Learning with Dual Gating Mixture-of-Experts for Robotic Manipulation
Cui Miao, Tao Chang, meihan wu et al.
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
Seung-Wook Kim, Seongyeol Kim, Jiah Kim et al.
FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning
Maximilian Hoefler, Karsten Mueller, Wojciech Samek
Feedback Favors the Generalization of Neural ODEs
Jindou Jia, Zihan Yang, Meng Wang et al.
FEEDBACK FRICTION: LLMs Struggle to Fully Incorporate External Feedback
Dongwei Jiang, Bowei Zhang, Andrew Wang et al.
Feedback Guidance of Diffusion Models
Felix Koulischer, Florian Handke, Johannes Deleu et al.
Feedback Schrödinger Bridge Matching
Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.
FeedEdit: Text-Based Image Editing with Dynamic Feedback Regulation
Fengyi Fu, Lei Zhang, Mengqi Huang et al.
Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos
hanxue liang, Jiawei Ren, Ashkan Mirzaei et al.
Feedforward Few-shot Species Range Estimation
Christian Lange, Max Hamilton, Elijah Cole et al.
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion
Aleksandar Jevtić, Christoph Reich, Felix Wimbauer et al.
Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown
Emile Anand, Sarah Liaw
FEEL: Quantifying Heterogeneity in Physiological Signals for Generalizable Emotion Recognition
Pragya Singh, Ankush Gupta, Somay Jalan et al.
Fengbo: a Clifford Neural Operator pipeline for 3D PDEs in Computational Fluid Dynamics
Alberto Pepe, Mattia Montanari, Joan Lasenby
Ferret: An Efficient Online Continual Learning Framework under Varying Memory Constraints
Yuhao Zhou, Yuxin Tian, Jindi Lv et al.