Dominic Richards

According to our database, Dominic Richards authored at least 16 papers between 2010 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Sparse Gaussian Processes with Spherical Harmonic Features Revisited.

Stefanos Eleftheriadis, Dominic Richards, James Hensman

CoRR, 2023

Formulating a method to analyse the differential expression of co-occurrence networks for small-sampled microbiome data.

Nandini Amit Gadhia, Michalis Smyrnakis, Po-Yu Liu, Damer Blake, Melanie Hay, Anh Nguyen, Dong Xia, Ritesh Krishna, Dominic Richards

Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

2022

Double Deep Q Networks for Sensor Management in Space Situational Awareness.

Benedict Oakes, Dominic Richards, Jordi Barr, Jason F. Ralph

Proceedings of the 25th International Conference on Information Fusion, 2022

2021

Multi-agent learning

Dominic Richards

PhD thesis, 2021

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

Dominic Richards, Edgar Dobriban, Patrick Rebeschini

CoRR, 2021

Distributed Machine Learning with Sparse Heterogeneous Data.

Dominic Richards, Sahand Negahban, Patrick Rebeschini

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Dominic Richards, Ilja Kuzborskij

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning with Gradient Descent and Weakly Convex Losses.

Dominic Richards, Mike Rabbat

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Asymptotics of Ridge(less) Regression under General Source Condition.

Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent.

Dominic Richards, Patrick Rebeschini

J. Mach. Learn. Res., 2020

Decentralised Learning with Random Features and Distributed Gradient Descent.

Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

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

Dominic Richards, Patrick Rebeschini

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2013

SpiNNaker: Fault tolerance in a power- and area- constrained large-scale neuromimetic architecture.

Javier Navaridas, Steve B. Furber, Jim D. Garside, Xin Jin, Mukaram M. Khan, David R. Lester, Mikel Luján, José Miguel-Alonso, Eustace Painkras, Cameron Patterson, Luis A. Plana, Alexander D. Rast, Dominic Richards, Yebin Shi, Steve Temple, Jian Wu, Shufan Yang

Parallel Comput., 2013

2011

Event-driven configuration of a neural network CMP system over an homogeneous interconnect fabric.

Mukaram M. Khan, Alexander D. Rast, Javier Navaridas, X. Jin, Luis A. Plana, Mikel Luján, Steve Temple, Cameron Patterson, Dominic Richards, John V. Woods, José Miguel-Alonso, Stephen B. Furber

Parallel Comput., 2011

A monadic approach to automated reasoning for Bluespec SystemVerilog.

Dominic Richards, David R. Lester

Innov. Syst. Softw. Eng., 2011

2010

A Prototype Embedding of Bluespec SystemVerilog in the PVS Theorem Prover.

Dominic Richards, David R. Lester

Proceedings of the Second NASA Formal Methods Symposium, 2010