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02/26/2023
Semi-supervised Gaussian mixture modelling with a missing-data mechanism in R
Semi-supervised learning is being extensively applied to estimate classi...
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10/25/2022
Some Simulation and Empirical Results for Semi-Supervised Learning of the Bayes Rule of Allocation
There has been increasing attention to semi-supervised learning (SSL) ap...
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01/03/2022
On randomized sketching algorithms and the Tracy-Widom law
There is an increasing body of work exploring the integration of random ...
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04/08/2021
Semi-Supervised Learning of Classifiers from a Statistical Perspective: A Brief Review
There has been increasing attention to semi-supervised learning (SSL) ap...
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04/07/2021
Data-fusion using factor analysis and low-rank matrix completion
Data-fusion involves the integration of multiple related datasets. The s...
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04/07/2021
Harmless label noise and informative soft-labels in supervised classification
Manual labelling of training examples is common practice in supervised l...
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04/13/2020
Estimation of Classification Rules from Partially Classified Data
We consider the situation where the observed sample contains some observ...
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10/21/2019
An Apparent Paradox: A Classifier Trained from a Partially Classified Sample May Have Smaller Expected Error Rate Than That If the Sample Were Completely Classified
There has been increasing interest in using semi-supervised learning to ...
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10/10/2019
Distributed Bayesian Computation for Model Choice
We propose a general method for distributed Bayesian model choice, where...
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10/10/2019
Distributed Computation for Marginal Likelihood based Model Choice
We propose a general method for distributed Bayesian model choice, using...
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04/05/2019
On missing label patterns in semi-supervised learning
We investigate model based classification with partially labelled traini...
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03/29/2019