Search Results for author: Zachary Kenton

Found 7 papers, 3 papers with code

Safe Deep RL in 3D Environments using Human Feedback

no code implementations20 Jan 2022 Matthew Rahtz, Vikrant Varma, Ramana Kumar, Zachary Kenton, Shane Legg, Jan Leike

In this paper we answer this question in the affirmative, using ReQueST to train an agent to perform a 3D first-person object collection task using data entirely from human contractors.

Alignment of Language Agents

no code implementations26 Mar 2021 Zachary Kenton, Tom Everitt, Laura Weidinger, Iason Gabriel, Vladimir Mikulik, Geoffrey Irving

For artificial intelligence to be beneficial to humans the behaviour of AI agents needs to be aligned with what humans want.

A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks

1 code implementation22 Dec 2019 Angelos Filos, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal

From our comparison we conclude that some current techniques which solve benchmarks such as UCI `overfit' their uncertainty to the dataset---when evaluated on our benchmark these underperform in comparison to simpler baselines.

Out-of-Distribution Detection

Generalizing from a few environments in safety-critical reinforcement learning

1 code implementation2 Jul 2019 Zachary Kenton, Angelos Filos, Owain Evans, Yarin Gal

Before deploying autonomous agents in the real world, we need to be confident they will perform safely in novel situations.

reinforcement-learning

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length

1 code implementation ICLR 2019 Stanisław Jastrzębski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos Storkey

When studying the SGD dynamics in relation to the sharpest directions in this initial phase, we find that the SGD step is large compared to the curvature and commonly fails to minimize the loss along the sharpest directions.

Three Factors Influencing Minima in SGD

no code implementations ICLR 2018 Stanisław Jastrzębski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos Storkey

In particular we find that the ratio of learning rate to batch size is a key determinant of SGD dynamics and of the width of the final minima, and that higher values of the ratio lead to wider minima and often better generalization.

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