A comprehensive survey of continual learning: theory, method and application
To cope with real-world dynamics, an intelligent system needs to incrementally acquire,
update, accumulate, and exploit knowledge throughout its lifetime. This ability, known as …
update, accumulate, and exploit knowledge throughout its lifetime. This ability, known as …
Deep class-incremental learning: A survey
Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
Computationally budgeted continual learning: What does matter?
A Prabhu, HA Al Kader Hammoud… - Proceedings of the …, 2023 - openaccess.thecvf.com
Continual Learning (CL) aims to sequentially train models on streams of incoming data that
vary in distribution by preserving previous knowledge while adapting to new data. Current …
vary in distribution by preserving previous knowledge while adapting to new data. Current …
Class-incremental continual learning into the extended der-verse
The staple of human intelligence is the capability of acquiring knowledge in a continuous
fashion. In stark contrast, Deep Networks forget catastrophically and, for this reason, the sub …
fashion. In stark contrast, Deep Networks forget catastrophically and, for this reason, the sub …
Pcr: Proxy-based contrastive replay for online class-incremental continual learning
Online class-incremental continual learning is a specific task of continual learning. It aims to
continuously learn new classes from data stream and the samples of data stream are seen …
continuously learn new classes from data stream and the samples of data stream are seen …
Continual learning of large language models: A comprehensive survey
The recent success of large language models (LLMs) trained on static, pre-collected,
general datasets has sparked numerous research directions and applications. One such …
general datasets has sparked numerous research directions and applications. One such …
Online prototype learning for online continual learning
Online continual learning (CL) studies the problem of learning continuously from a single-
pass data stream while adapting to new data and mitigating catastrophic forgetting …
pass data stream while adapting to new data and mitigating catastrophic forgetting …
Real-time evaluation in online continual learning: A new hope
Abstract Current evaluations of Continual Learning (CL) methods typically assume that there
is no constraint on training time and computation. This is an unrealistic assumption for any …
is no constraint on training time and computation. This is an unrealistic assumption for any …
On the effectiveness of lipschitz-driven rehearsal in continual learning
Rehearsal approaches enjoy immense popularity with Continual Learning (CL)
practitioners. These methods collect samples from previously encountered data distributions …
practitioners. These methods collect samples from previously encountered data distributions …
Class-incremental learning: A survey
Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
in many vision tasks in the closed world. However, novel classes emerge from time to time in …