论文中特别提到了类增量学习(class-incremental learning)的设置。视觉-语言模型(Vision-Language Models, VLMs)的微调: 预训练的VLMs(如CLIP)在下游任务上的应用。 微调方法,包括特征适配器模块、软提示学习等。 论文中讨论了这些方法在持续学习中的局限性。概率...
Table 1. Non-IID learning scenarios in Federated Learning, and the strategies that could potentially solve each situation. Strategies that deal with changes in both the input space and the behaviour are placed only in the last column, and not in the previous ones. 3.2. State-of-the-art clas...
Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685, 2021. 3 [19] Zixuan Ke, Bing Liu, and Xingchang Huang. Continual learning of a mixed sequence of similar and dissimilar tasks. NeurIPS, 33, 2020. 1, 3, 5 [20] Diederik P Kingma and Jimmy Ba. Adam...
Continual Learning learn non-stationary data distribution without forgetting previous knowledge data-distribution shift during training Foundation Model unsupervised learning on large-scale unlabeled data data-distribution shift in pre-training, fine-tuning Domain Adaptation adapt to target domain while maintaini...
Disentangled Continual Learning: Separating Memory Edits from Model Updates [PDF2] Authors: Sebastian Dziadzio ; Çağatay Yıldız ; Gido M. van de Ven ; Tomasz Trzciński ; Tinne Tuytelaars ; Matt…
In this paper, we propose orthogonal low-rank adaptation (O-LoRA), a simple and efficient approach for continual learning in language models, effectively mitigating catastrophic forgetting while learning new tasks. Specifically, O-LoRA learns tasks in different (low-rank) vector subspaces that are ...
A low stable rank means that the units of a network do not provide much diversity; the base deep-learning system loses much more diversity than the Shrink and Perturb and continual backpropagation systems. All results are averaged over 30 runs; the solid lines represent the mean and the shade...
[FSCIL] Few-shot Class Incremental Learning [Link] [DCIL] Decentralized Class Incremental Learning [paper][Setting] 3 Papers by Categories Tips: you can use ctrl+F to match abbreviations with articles, or browse the paper list below. 3.1 From an Algorithm Perspective Network StructureRehears...
Decision trees are well-known and attractive learning algorithms for data streams, offering low computational cost with excellent adaptation capabilities to concept drift (Gomes et al. 2019). Furthermore, they are explainable and interpretable models, offering white-box approach for streaming data. ...
A low stable rank means that the units of a network do not provide much diversity; the base deep-learning system loses much more diversity than the Shrink and Perturb and continual backpropagation systems. All results are averaged over 30 runs; the solid lines represent the mean and the shade...