4 papers
Learning to Forget: Continual Learning with Adaptive Weight Decay
Aditya A. Ramesh, Alex Lewandowski, Jürgen Schmidhuber
Continual learning agents with finite capacity must balance acquiring new knowledge with retaining the old. This requires controlled forgetting of knowledge that is no longer neede…
Universal computation is intrinsic to language model decoding
Alex Lewandowski, Marlos C. Machado, Dale Schuurmans
Language models now provide an interface to express and often solve general problems in natural language, yet their ultimate computational capabilities remain a major topic of scie…
The World Is Bigger! A Computationally-Embedded Perspective on the Big World Hypothesis
Alex Lewandowski, Adtiya A. Ramesh, Edan Meyer +2
Continual learning is often motivated by the idea, known as the big world hypothesis, that "the world is bigger" than the agent. Recent problem formulations capture this idea by ex…
Plastic Learning with Deep Fourier Features
Alex Lewandowski, Dale Schuurmans, Marlos C. Machado
Deep neural networks can struggle to learn continually in the face of non-stationarity. This phenomenon is known as loss of plasticity. In this paper, we identify underlying princi…