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03/15/2023
Bayesian Quadrature for Neural Ensemble Search
Ensembling can improve the performance of Neural Networks, but existing ...
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06/13/2020
Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel
Bayesian optimisation (BO) has been widely used for hyperparameter optim...
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12/19/2019
A Maximum Entropy approach to Massive Graph Spectra
Graph spectral techniques for measuring graph similarity, or for learnin...
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07/01/2019
Radial Bayesian Neural Networks: Robust Variational Inference In Big Models
We propose Radial Bayesian Neural Networks: a variational distribution f...
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06/03/2019
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning
Efficient approximation lies at the heart of large-scale machine learnin...
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01/25/2019
On the Limitations of Representing Functions on Sets
Recent work on the representation of functions on sets has considered th...
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12/04/2018
Batch Selection for Parallelisation of Bayesian Quadrature
Integration over non-negative integrands is a central problem in machine...
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11/25/2018
Intersectionality: Multiple Group Fairness in Expectation Constraints
Group fairness is an important concern for machine learning researchers,...
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10/10/2018
Equality Constrained Decision Trees: For the Algorithmic Enforcement of Group Fairness
Fairness, through its many forms and definitions, has become an importan...
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04/18/2018
Entropic Spectral Learning in Large Scale Networks
We present a novel algorithm for learning the spectral density of large ...
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02/21/2018
VBALD - Variational Bayesian Approximation of Log Determinants
Evaluating the log determinant of a positive definite matrix is ubiquito...
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11/12/2017
Sensor Selection and Random Field Reconstruction for Robust and Cost-effective Heterogeneous Weather Sensor Networks for the Developing World
We address the two fundamental problems of spatial field reconstruction ...
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11/02/2017
Fast Information-theoretic Bayesian Optimisation
Information-theoretic Bayesian optimisation techniques have demonstrated...
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04/24/2017
Entropic Trace Estimates for Log Determinants
The scalable calculation of matrix determinants has been a bottleneck to...
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04/05/2017
Bayesian Inference of Log Determinants
The log-determinant of a kernel matrix appears in a variety of machine l...
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10/21/2015
GLASSES: Relieving The Myopia Of Bayesian Optimisation
We present GLASSES: Global optimisation with Look-Ahead through Stochast...
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07/02/2015
Anomaly Detection and Removal Using Non-Stationary Gaussian Processes
This paper proposes a novel Gaussian process approach to fault removal i...
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03/18/2014
Communication Communities in MOOCs
Massive Open Online Courses (MOOCs) bring together thousands of people f...
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02/17/2014