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20192023
most citedNew Insights on Reducing Abrupt Representation Change in Online Continual Learning

45 citations · 80 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.LG2023★ 3 cited

Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning

Nader Asadi, MohammadReza Davari, Sudhir Mudur +2

In Continual learning (CL) balancing effective adaptation while combating catastrophic forgetting is a central challenge. Many of the recent best-performing methods utilize various…

cs.LG2022

New Insights on Reducing Abrupt Representation Change in Online Continual Learning

Lucas Caccia, Rahaf Aljundi, Nader Asadi +3

In the online continual learning paradigm, agents must learn from a changing distribution while respecting memory and compute constraints. Experience Replay (ER), where a small sub…

cs.LG2022★ 4 cited

Probing Representation Forgetting in Supervised and Unsupervised Continual Learning

MohammadReza Davari, Nader Asadi, Sudhir Mudur +2

Continual Learning research typically focuses on tackling the phenomenon of catastrophic forgetting in neural networks. Catastrophic forgetting is associated with an abrupt loss of…

cs.LG2022

Tackling Online One-Class Incremental Learning by Removing Negative Contrasts

Nader Asadi, Sudhir Mudur, Eugene Belilovsky

Recent work studies the supervised online continual learning setting where a learner receives a stream of data whose class distribution changes over time. Distinct from other conti…

cs.LG2021★ 45 cited

New Insights on Reducing Abrupt Representation Change in Online Continual Learning

Lucas Caccia, Rahaf Aljundi, Nader Asadi +3

In the online continual learning paradigm, agents must learn from a changing distribution while respecting memory and compute constraints. Experience Replay (ER), where a small sub…