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09/05/2023
Backward error analysis and the qualitative behaviour of stochastic optimization algorithms: Application to stochastic coordinate descent
Stochastic optimization methods have been hugely successful in making la...
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05/15/2023
On the connections between optimization algorithms, Lyapunov functions, and differential equations: theory and insights
We study connections between differential equations and optimization alg...
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02/09/2023
Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures
Bayesian posterior distributions arising in modern applications, includi...
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09/10/2022
Batch Bayesian Optimization via Particle Gradient Flows
Bayesian Optimisation (BO) methods seek to find global optima of objecti...
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07/28/2022
Generative Hypergraph Models and Spectral Embedding
Many complex systems involve interactions between more than two agents. ...
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01/22/2022
The Forward-Backward Envelope for Sampling with the Overdamped Langevin Algorithm
In this paper, we analyse a proximal method based on the idea of forward...
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08/27/2020
Implicit Regularization in Matrix Sensing: A Geometric View Leads to Stronger Results
We may think of low-rank matrix sensing as a learning problem with infin...
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10/26/2016
Probabilistic Linear Multistep Methods
We present a derivation and theoretical investigation of the Adams-Bashf...
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09/15/2016
Multilevel Monte Carlo for Scalable Bayesian Computations
Markov chain Monte Carlo (MCMC) algorithms are ubiquitous in Bayesian co...
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05/04/2016