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09/11/2020
Bayesian Beta-Binomial Prevalence Estimation Using an Imperfect Test
Following [Diggle 2011, Greenland 1995], we give a simple formula for th...
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02/27/2020
Theoretical Models of Learning to Learn
A Machine can only learn if it is biased in some way. Typically the bias...
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11/18/2019
General Matrix-Matrix Multiplication Using SIMD features of the PIII
Generalised matrix-matrix multiplication forms the kernel of many mathem...
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11/17/2019
Hebbian Synaptic Modifications in Spiking Neurons that Learn
In this paper, we derive a new model of synaptic plasticity, based on re...
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11/14/2019
The Canonical Distortion Measure for Vector Quantization and Function Approximation
To measure the quality of a set of vector quantization points a means of...
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11/14/2019
Learning Model Bias
In this paper the problem of learning appropriate domain-specific bias ...
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11/14/2019
A Bayesian/Information Theoretic Model of Bias Learning
In this paper the problem of learning appropriate bias for an environmen...
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11/12/2019
92c/MFlops/s, Ultra-Large-Scale Neural-Network Training on a PIII Cluster
Artificial neural networks with millions of adjustable parameters and a ...
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11/09/2019
Learning Internal Representations
Most machine learning theory and practice is concerned with learning a s...
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11/09/2019
Learning Internal Representations (PhD Thesis)
Most machine learning theory and practice is concerned with learning a s...
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01/10/1999
KnightCap: A chess program that learns by combining TD(lambda) with game-tree search
In this paper we present TDLeaf(lambda), a variation on the TD(lambda) a...
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01/05/1999