Imagen de Portada

Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wu, Beining, Huang, Jun
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Mobile Application for Oral Disease Detection using Federated Learning
por: Narayanan V, Shankara, et al.
Publicado: (2023)

Domain-Aware Continual Zero-Shot Learning
por: Yi, Kai, et al.
Publicado: (2021)

CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model
por: Hou, Shihao, et al.
Publicado: (2025)

Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning
por: Qi, Xiaoming, et al.
Publicado: (2025)

FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework
por: He, Yuchen, et al.
Publicado: (2024)

Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search
por: Yu, Sixing, et al.
Publicado: (2022)

Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning
por: Liang, Jinglin, et al.
Publicado: (2024)

Dynamic Feedback Engines: Layer-Wise Control for Self-Regulating Continual Learning
por: Wu, Hengyi, et al.
Publicado: (2025)

Continuous Subspace Optimization for Continual Learning
por: Cheng, Quan, et al.
Publicado: (2025)

Remembering Transformer for Continual Learning
por: Sun, Yuwei, et al.
Publicado: (2024)

Continual Learning for Autonomous Robots: A Prototype-based Approach
por: Hajizada, Elvin, et al.
Publicado: (2024)

CARIL: Confidence-Aware Regression in Imitation Learning for Autonomous Driving
por: Delavari, Elahe, et al.
Publicado: (2025)

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models
por: Luo, Jun, et al.
Publicado: (2024)

Consistent Prompting for Rehearsal-Free Continual Learning
por: Gao, Zhanxin, et al.
Publicado: (2024)

Context-Based Semantic-Aware Alignment for Semi-Supervised Multi-Label Learning
por: Fan, Heng-Bo, et al.
Publicado: (2024)

FMCL: Class-Aware Client Clustering with Foundation Model Representations for Heterogeneous Federated Learning
por: Ali, Mahad, et al.
Publicado: (2026)

C^2Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
por: Xu, Kunlun, et al.
Publicado: (2025)

FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning
por: Rajib, Rakibul Hasan, et al.
Publicado: (2025)

Federated Balanced Learning
por: Li, Jiaze, et al.
Publicado: (2026)

On the Federated Learning Framework for Cooperative Perception
por: Zhang, Zhenrong, et al.
Publicado: (2024)

Continual Adaptation of Vision Transformers for Federated Learning
por: Halbe, Shaunak, et al.
Publicado: (2023)

Rehearsal-free and Task-free Online Continual Learning With Contrastive Prompt
por: Wang, Aopeng, et al.
Publicado: (2025)

Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing
por: Qiao, Zhongzheng, et al.
Publicado: (2024)

C$^{2}$INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention
por: Li, Xiaohe, et al.
Publicado: (2024)

Scaling-Aware Data Selection for End-to-End Autonomous Driving Systems
por: Dimlioglu, Tolga, et al.
Publicado: (2026)

Stable-Drift: A Patient-Aware Latent Drift Replay Method for Stabilizing Representations in Continual Learning
por: Theofilou, Paraskevi-Antonia, et al.
Publicado: (2025)

FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise
por: Wu, Nannan, et al.
Publicado: (2023)

Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving
por: Wu, Yang, et al.
Publicado: (2026)

RMT-PPAD: Real-time Multi-task Learning for Panoptic Perception in Autonomous Driving
por: Wang, Jiayuan, et al.
Publicado: (2025)

Densely Distilling Cumulative Knowledge for Continual Learning
por: Shi, Zenglin, et al.
Publicado: (2024)

Interactive Continual Learning: Fast and Slow Thinking
por: Qi, Biqing, et al.
Publicado: (2024)

An Experimental Study of Semantic Continuity for Deep Learning Models
por: Wu, Shangxi, et al.
Publicado: (2020)

InfLoRA: Interference-Free Low-Rank Adaptation for Continual Learning
por: Liang, Yan-Shuo, et al.
Publicado: (2024)

From Selection to Scheduling: Federated Geometry-Aware Correction Makes Exemplar Replay Work Better under Continual Dynamic Heterogeneity
por: Qi, Zhuang, et al.
Publicado: (2026)

Continuously Improving Mobile Manipulation with Autonomous Real-World RL
por: Mendonca, Russell, et al.
Publicado: (2024)

Mobi-$π$: Mobilizing Your Robot Learning Policy
por: Yang, Jingyun, et al.
Publicado: (2025)

Adaptive Retention & Correction: Test-Time Training for Continual Learning
por: Chen, Haoran, et al.
Publicado: (2024)

Exploiting T-norms for Deep Learning in Autonomous Driving
por: Stoian, Mihaela Cătălina, et al.
Publicado: (2024)

Continual Distillation Learning: Knowledge Distillation in Prompt-based Continual Learning
por: Zhang, Qifan, et al.
Publicado: (2024)

Personalized Longitudinal Medical Report Generation via Temporally-Aware Federated Adaptation
por: Zhu, He, et al.
Publicado: (2026)