Joel Veness | DeepAI

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∙ 09/19/2023

Language Modeling Is Compression

It has long been established that predictive models can be transformed i...

0 Grégoire Delétang, et al. ∙

∙ 05/26/2023

Randomized Positional Encodings Boost Length Generalization of Transformers

Transformers have impressive generalization capabilities on tasks with a...

0 Anian Ruoss, et al. ∙

∙ 02/06/2023

Memory-Based Meta-Learning on Non-Stationary Distributions

Memory-based meta-learning is a technique for approximating Bayes-optima...

0 Tim Genewein, et al. ∙

∙ 09/30/2022

Beyond Bayes-optimality: meta-learning what you know you don't know

Meta-training agents with memory has been shown to culminate in Bayes-op...

8 Jordi Grau-Moya, et al. ∙

∙ 10/20/2021

Shaking the foundations: delusions in sequence models for interaction and control

The recent phenomenal success of language models has reinvigorated machi...

68 Pedro A. Ortega, et al. ∙

∙ 09/30/2021

Reinforcement Learning with Information-Theoretic Actuation

Reinforcement Learning formalises an embodied agent's interaction with t...

16 Elliot Catt, et al. ∙

∙ 10/23/2020

A Combinatorial Perspective on Transfer Learning

Human intelligence is characterized not only by the capacity to learn co...

98 Jianan Wang, et al. ∙

∙ 06/10/2020

Gaussian Gated Linear Networks

We propose the Gaussian Gated Linear Network (G-GLN), an extension to th...

12 David Budden, et al. ∙

∙ 02/21/2020

Online Learning in Contextual Bandits using Gated Linear Networks

We introduce a new and completely online contextual bandit algorithm cal...

1 Eren Sezener, et al. ∙

∙ 09/30/2019

Gated Linear Networks

This paper presents a family of backpropagation-free neural architecture...

38 Joel Veness, et al. ∙

∙ 05/08/2019

Meta-learning of Sequential Strategies

In this report we review memory-based meta-learning as a tool for buildi...

16 Pedro A. Ortega, et al. ∙

∙ 12/05/2017

Online Learning with Gated Linear Networks

This paper describes a family of probabilistic architectures designed fo...

0 Joel Veness, et al. ∙

∙ 12/02/2016

Overcoming catastrophic forgetting in neural networks

The ability to learn tasks in a sequential fashion is crucial to the dev...

0 James Kirkpatrick, et al. ∙

∙ 11/19/2014

Compress and Control

This paper describes a new information-theoretic policy evaluation techn...

0 Joel Veness, et al. ∙

∙ 11/03/2012

Partition Tree Weighting

This paper introduces the Partition Tree Weighting technique, an efficie...

0 Joel Veness, et al. ∙

∙ 07/19/2012

The Arcade Learning Environment: An Evaluation Platform for General Agents

In this article we introduce the Arcade Learning Environment (ALE): both...

0 Marc G. Bellemare, et al. ∙

∙ 09/27/2011

An Approximation of the Universal Intelligence Measure

The Universal Intelligence Measure is a recently proposed formal definit...

0 Shane Legg, et al. ∙

∙ 09/04/2009

A Monte Carlo AIXI Approximation

This paper introduces a principled approach for the design of a scalable...

0 Joel Veness, et al. ∙

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