Copertina

Class-wise Balancing Data Replay for Federated Class-Incremental Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Qi, Zhuang, Tang, Ying-Peng, Meng, Lei, Yu, Han, Li, Xiaoxiao, Meng, Xiangxu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

CCSI: Continual Class-Specific Impression for Data-free Class Incremental Learning
di: Ayromlou, Sana, et al.
Pubblicazione: (2024)

Towards Experience Replay for Class-Incremental Learning in Fully-Binary Networks
di: Basso-Bert, Yanis, et al.
Pubblicazione: (2025)

Global Prompt Refinement with Non-Interfering Attention Masking for One-Shot Federated Learning
di: Qi, Zhuang, et al.
Pubblicazione: (2025)

Class-Incremental Learning: A Survey
di: Zhou, Da-Wei, et al.
Pubblicazione: (2023)

Generative Binary Memory: Pseudo-Replay Class-Incremental Learning on Binarized Embeddings
di: Basso-Bert, Yanis, et al.
Pubblicazione: (2025)

Closing the Oracle Gap: Increment Vector Transformation for Class Incremental Learning
di: Qiu, Zihuan, et al.
Pubblicazione: (2025)

Cross-Class Feature Augmentation for Class Incremental Learning
di: Kim, Taehoon, et al.
Pubblicazione: (2023)

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

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization
di: Qi, Zhuang, et al.
Pubblicazione: (2025)

Effective Decision Boundary Learning for Class Incremental Learning
di: Li, Kunchi, et al.
Pubblicazione: (2023)

Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning
di: Qi, Zhi-Hong, et al.
Pubblicazione: (2024)

Text-Enhanced Data-free Approach for Federated Class-Incremental Learning
di: Tran, Minh-Tuan, et al.
Pubblicazione: (2024)

Towards Fair Class-wise Robustness: Class Optimal Distribution Adversarial Training
di: Zhi, Hongxin, et al.
Pubblicazione: (2025)

Future-Proofing Class-Incremental Learning
di: Jodelet, Quentin, et al.
Pubblicazione: (2024)

When Classes Evolve: A Benchmark and Framework for Stage-Aware Class-Incremental Learning
di: Zhang, Zheng, et al.
Pubblicazione: (2026)

External Knowledge Injection for CLIP-Based Class-Incremental Learning
di: Zhou, Da-Wei, et al.
Pubblicazione: (2025)

PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning
di: Ma'sum, Muhammad Anwar, et al.
Pubblicazione: (2024)

DS-AL: A Dual-Stream Analytic Learning for Exemplar-Free Class-Incremental Learning
di: Zhuang, Huiping, et al.
Pubblicazione: (2024)

Towards Class-wise Robustness Analysis
di: Medi, Tejaswini, et al.
Pubblicazione: (2024)

Confidence Self-Calibration for Multi-Label Class-Incremental Learning
di: Du, Kaile, et al.
Pubblicazione: (2024)

AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning
di: Xie, Zhen-Hao, et al.
Pubblicazione: (2026)

Stable Routing for Mixture-of-Experts in Class-Incremental Learning
di: Guo, Zirui, et al.
Pubblicazione: (2026)

Specifying What You Know or Not for Multi-Label Class-Incremental Learning
di: Zhang, Aoting, et al.
Pubblicazione: (2025)

12 mJ per Class On-Device Online Few-Shot Class-Incremental Learning
di: Wibowo, Yoga Esa, et al.
Pubblicazione: (2024)

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning
di: Zhou, Da-Wei, et al.
Pubblicazione: (2024)

Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory
di: Wang, Naibo, et al.
Pubblicazione: (2024)

Merge and Bound: Direct Manipulations on Weights for Class Incremental Learning
di: Kim, Taehoon, et al.
Pubblicazione: (2025)

Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning
di: Liu, Jiaming, et al.
Pubblicazione: (2024)

Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation
di: Kwak, Jihwan, et al.
Pubblicazione: (2024)

Hierarchical Semantic Tree Anchoring for CLIP-Based Class-Incremental Learning
di: Hu, Tao, et al.
Pubblicazione: (2025)

Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning
di: Jiang, Kai, et al.
Pubblicazione: (2025)

iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning
di: Fischer, Tom, et al.
Pubblicazione: (2024)

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
di: Sun, Hai-Long, et al.
Pubblicazione: (2024)

BOFA: Bridge-Layer Orthogonal Low-Rank Fusion for CLIP-Based Class-Incremental Learning
di: Li, Lan, et al.
Pubblicazione: (2025)

On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning
di: Fang, Pengfei, et al.
Pubblicazione: (2024)

A Bag of Tricks for Few-Shot Class-Incremental Learning
di: Roy, Shuvendu, et al.
Pubblicazione: (2024)

Understanding Imbalanced Forgetting in Rehearsal-Based Class-Incremental Learning
di: Tamajo, Alberto, et al.
Pubblicazione: (2026)

Scalable Class-Incremental Learning Based on Parametric Neural Collapse
di: Zhang, Chuangxin, et al.
Pubblicazione: (2025)

Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning
di: Zhao, Haifeng, et al.
Pubblicazione: (2024)