
Neural Architecture Search using Bayesian Optimisation with WeisfeilerLehman Kernel
Bayesian optimisation (BO) has been widely used for hyperparameter optim...
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A Maximum Entropy approach to Massive Graph Spectra
Graph spectral techniques for measuring graph similarity, or for learnin...
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Radial Bayesian Neural Networks: Robust Variational Inference In Big Models
We propose Radial Bayesian Neural Networks: a variational distribution f...
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MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in LargeScale Machine Learning
Efficient approximation lies at the heart of largescale machine learnin...
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On the Limitations of Representing Functions on Sets
Recent work on the representation of functions on sets has considered th...
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Batch Selection for Parallelisation of Bayesian Quadrature
Integration over nonnegative integrands is a central problem in machine...
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Intersectionality: Multiple Group Fairness in Expectation Constraints
Group fairness is an important concern for machine learning researchers,...
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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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Entropic Spectral Learning in Large Scale Networks
We present a novel algorithm for learning the spectral density of large ...
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VBALD  Variational Bayesian Approximation of Log Determinants
Evaluating the log determinant of a positive definite matrix is ubiquito...
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Sensor Selection and Random Field Reconstruction for Robust and Costeffective Heterogeneous Weather Sensor Networks for the Developing World
We address the two fundamental problems of spatial field reconstruction ...
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Fast Informationtheoretic Bayesian Optimisation
Informationtheoretic Bayesian optimisation techniques have demonstrated...
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Entropic Trace Estimates for Log Determinants
The scalable calculation of matrix determinants has been a bottleneck to...
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Bayesian Inference of Log Determinants
The logdeterminant of a kernel matrix appears in a variety of machine l...
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GLASSES: Relieving The Myopia Of Bayesian Optimisation
We present GLASSES: Global optimisation with LookAhead through Stochast...
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Anomaly Detection and Removal Using NonStationary Gaussian Processes
This paper proposes a novel Gaussian process approach to fault removal i...
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Communication Communities in MOOCs
Massive Open Online Courses (MOOCs) bring together thousands of people f...
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Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space
Existing work in multiagent collision prediction and avoidance typicall...
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Michael Osborne
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