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Accelerated gradient temporal difference learning
The family of temporal difference (TD) methods span a spectrum from computationally frugal
linear methods like TD (λ) to data efficient least squares methods. Least square methods …
linear methods like TD (λ) to data efficient least squares methods. Least square methods …
Meta-descent for online, continual prediction
This paper investigates different vector step-size adaptation approaches for non-stationary
online, continual prediction problems. Vanilla stochastic gradient descent can be …
online, continual prediction problems. Vanilla stochastic gradient descent can be …
Representation alignment in neural networks
Improving Sample Efficiency of Online Temporal Difference Learning
Y Pan - 2021 - era.library.ualberta.ca
A common scientific challenge for putting a reinforcement learning agent into practice is how
to improve sample efficiency as much as possible with limited computational or memory …
to improve sample efficiency as much as possible with limited computational or memory …
Vector Step-size Adaptation for Continual, Online Prediction
A Jacobsen - 2019 - era.library.ualberta.ca
In this thesis, we investigate different vector step-size adaptation approaches for continual,
online prediction problems. Vanilla stochastic gradient descent can be considerably …
online prediction problems. Vanilla stochastic gradient descent can be considerably …