24 citations · 64 across the 6 of their papers we have counts for
6 papers
Learning Internal Representations (PhD Thesis)
Jonathan Baxter
Most machine learning theory and practice is concerned with learning a single task. In this thesis it is argued that in general there is insufficient information in a single task f…
Some observations concerning Off Training Set (OTS) error
Jonathan Baxter
A form of generalisation error known as Off Training Set (OTS) error was recently introduced in [Wolpert, 1996b], along with a theorem showing that small training set error does no…
Hebbian Synaptic Modifications in Spiking Neurons that Learn
Peter L. Bartlett, Jonathan Baxter
In this paper, we derive a new model of synaptic plasticity, based on recent algorithms for reinforcement learning (in which an agent attempts to learn appropriate actions to maxim…
The Canonical Distortion Measure for Vector Quantization and Function Approximation
Jonathan Baxter
To measure the quality of a set of vector quantization points a means of measuring the distance between a random point and its quantization is required. Common metrics such as the…
Learning Model Bias
Jonathan Baxter
In this paper the problem of {\em learning} appropriate domain-specific bias is addressed. It is shown that this can be achieved by learning many related tasks from the same domain…
A Bayesian/Information Theoretic Model of Bias Learning
Jonathan Baxter
In this paper the problem of learning appropriate bias for an environment of related tasks is examined from a Bayesian perspective. The environment of related tasks is shown to be…