Dominic Richards

23 papers A* 4A 2C 1Journal 13Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Novel Approach to Differential Expression Analysis of Co-Occurrence Networks for Small-Sampled Microbiome Data.
IEEE Trans. Comput. Biol. Bioinform.
Nandini Amit Gadhia, Michalis Smyrnakis, Po-Yu Liu, Damer Blake, Melanie Hay, Anh Nguyen, Dominic Richards, Dong Xia, Ritesh Krishna
2023 — conf
Formulating a method to analyse the differential expression of co-occurrence networks for small-sampled microbiome data.
BCB
Nandini Amit Gadhia, Michalis Smyrnakis, Po-Yu Liu, Damer Blake, Melanie Hay, Anh Nguyen, Dong Xia, Ritesh Krishna, Dominic Richards
2023 J jnl
Sparse Gaussian Processes with Spherical Harmonic Features Revisited.
CoRR
Stefanos Eleftheriadis, Dominic Richards, James Hensman
2022 C conf
Double Deep Q Networks for Sensor Management in Space Situational Awareness.
FUSION
Benedict Oakes, Dominic Richards, Jordi Barr, Jason F. Ralph
2022 J jnl
Double Deep Q Networks for Sensor Management in Space Situational Awareness.
CoRR
Benedict Oakes, Dominic Richards, Jordi Barr, Jason F. Ralph
2021 A conf
Asymptotics of Ridge(less) Regression under General Source Condition.
AISTATS
Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco
2021 J jnl
Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?
CoRR
Dominic Richards, Edgar Dobriban, Patrick Rebeschini
2021 A* conf
Distributed Machine Learning with Sparse Heterogeneous Data.
NeurIPS
Dominic Richards, Sahand Negahban, Patrick Rebeschini
2021 A conf
Learning with Gradient Descent and Weakly Convex Losses.
AISTATS
Dominic Richards, Mike Rabbat
2021 J jnl
Learning with Gradient Descent and Weakly Convex Losses.
CoRR
Dominic Richards, Mike Rabbat
2021 — —
Multi-agent learning
Dominic Richards
2021 A* conf
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel.
NeurIPS
Dominic Richards, Ilja Kuzborskij
2021 J jnl
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel.
CoRR
Dominic Richards, Ilja Kuzborskij
2020 A* conf
Decentralised Learning with Random Features and Distributed Gradient Descent.
ICML
Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco
2020 J jnl
Decentralised Learning with Random Features and Distributed Gradient Descent.
CoRR
Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco
2020 J jnl
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent.
J. Mach. Learn. Res.
Dominic Richards, Patrick Rebeschini
2019 A* conf
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up.
NeurIPS
Dominic Richards, Patrick Rebeschini
2019 J jnl
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up.
CoRR
Dominic Richards, Patrick Rebeschini
2018 J jnl
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent.
CoRR
Dominic Richards, Patrick Rebeschini
2013 J jnl
SpiNNaker: Fault tolerance in a power- and area- constrained large-scale neuromimetic architecture.
Parallel Comput.
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
2011 J jnl
A monadic approach to automated reasoning for Bluespec SystemVerilog.
Innov. Syst. Softw. Eng.
Dominic Richards, David R. Lester
2011 J jnl
Event-driven configuration of a neural network CMP system over an homogeneous interconnect fabric.
Parallel Comput.
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
2010 — conf
A Prototype Embedding of Bluespec SystemVerilog in the PVS Theorem Prover.
NASA Formal Methods
Dominic Richards, David R. Lester