Dominic Richards | DeepAI

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∙ 03/28/2023

Sparse Gaussian Processes with Spherical Harmonic Features Revisited

We revisit the Gaussian process model with spherical harmonic features a...

1 Stefanos Eleftheriadis, et al. ∙

∙ 05/27/2022

Double Deep Q Networks for Sensor Management in Space Situational Awareness

We present a novel Double Deep Q Network (DDQN) application to a sensor ...

0 Benedict Oakes, et al. ∙

∙ 08/26/2021

Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?

Modern methods for learning from data depend on many tuning parameters, ...

0 Dominic Richards, et al. ∙

∙ 07/27/2021

Stability Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel

We revisit on-average algorithmic stability of Gradient Descent (GD) for...

0 Dominic Richards, et al. ∙

∙ 01/13/2021

Learning with Gradient Descent and Weakly Convex Losses

We study the learning performance of gradient descent when the empirical...

0 Dominic Richards, et al. ∙

∙ 07/01/2020

Decentralised Learning with Random Features and Distributed Gradient Descent

We investigate the generalisation performance of Distributed Gradient De...

11 Dominic Richards, et al. ∙

∙ 06/11/2020

Asymptotics of Ridge(less) Regression under General Source Condition

We analyze the prediction performance of ridge and ridgeless regression ...

2 Dominic Richards, et al. ∙

∙ 12/03/2019

Decentralised Sparse Multi-Task Regression

We consider a sparse multi-task regression framework for fitting a colle...

17 Dominic Richards, et al. ∙

∙ 05/08/2019

Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up

We analyse the learning performance of Distributed Gradient Descent in t...

0 Dominic Richards, et al. ∙

∙ 09/18/2018

Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent

We propose graph-dependent implicit regularisation strategies for distri...

0 Dominic Richards, et al. ∙

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