Parameter-level soft-masking for continual learning

T Konishi, M Kurokawa, C Ono, Z Ke… - International …, 2023 - proceedings.mlr.press
Existing research on task incremental learning in continual learning has primarily focused
on preventing catastrophic forgetting (CF). Although several techniques have achieved …

An introduction to lifelong supervised learning

S Sodhani, M Faramarzi, SV Mehta, P Malviya… - arXiv preprint arXiv …, 2022 - arxiv.org
This primer is an attempt to provide a detailed summary of the different facets of lifelong
learning. We start with Chapter 2 which provides a high-level overview of lifelong learning …

Continual Learning and Catastrophic Forgetting

GM van de Ven, N Soures, D Kudithipudi - arXiv preprint arXiv:2403.05175, 2024 - arxiv.org
This book chapter delves into the dynamics of continual learning, which is the process of
incrementally learning from a non-stationary stream of data. Although continual learning is a …

Representation ensembling for synergistic lifelong learning with quasilinear complexity

JT Vogelstein, J Dey, HS Helm, W LeVine… - arXiv preprint arXiv …, 2020 - arxiv.org
In lifelong learning, data are used to improve performance not only on the current task, but
also on previously encountered, and as yet unencountered tasks. In contrast, classical …

OUT-OF-DISTRIBUTION LEARNING

J Dey - 2024 - jscholarship.library.jhu.edu
Traditional machine learning approaches assume data points are independent and
identically distributed (iid). However, in practice, a learning agent may face data points …