research
∙
03/14/2023
Is forgetting less a good inductive bias for forward transfer?
One of the main motivations of studying continual learning is that the p...
share
research
∙
10/28/2022
When does mixup promote local linearity in learned representations?
Mixup is a regularization technique that artificially produces new sampl...
research
∙
02/01/2022
Architecture Matters in Continual Learning
A large body of research in continual learning is devoted to overcoming ...
research
∙
10/21/2021
Wide Neural Networks Forget Less Catastrophically
A growing body of research in continual learning is devoted to overcomin...
research
∙
08/02/2021
Multilevel Knowledge Transfer for Cross-Domain Object Detection
Domain shift is a well known problem where a model trained on a particul...
research
∙
10/22/2020
Continual Learning in Low-rank Orthogonal Subspaces
In continual learning (CL), a learner is faced with a sequence of tasks,...
research
∙
02/19/2020
Using Hindsight to Anchor Past Knowledge in Continual Learning
In continual learning, the learner faces a stream of data whose distribu...
research
∙
02/27/2019
Continual Learning with Tiny Episodic Memories
Learning with less supervision is a major challenge in artificial intell...
research
∙
12/02/2018
Efficient Lifelong Learning with A-GEM
In lifelong learning, the learner is presented with a sequence of tasks,...
research
∙
01/30/2018
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
We study the incremental learning problem for the classification task, a...
research
∙
07/18/2017
