Dominic Richards
7 papers · 2019–2021 · 4 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (4) π Cross-Pollinator (8) πΊοΈ Taxonomy Completionist (18)
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Hot Topic Early Bird
Conferences
NIPS (3)
AISTATS (2)
ICML (1)
JMLR (1)
Top co-authors
Research topics
Keywords
distributed learning
(3)
gradient descent
(3)
neural network
(2)
algorithmic stability
(2)
implicit regularization
(2)
asymptotic analysis
(1)
distributed optimization
(1)
convex optimization
(1)
generalization bound
(1)
generalization error
(1)
signal-to-noise ratio
(1)
kernel regression
(1)
non-parametric regression
(1)
excess risk
(1)
graph topology
(1)
multi-agent learning
(1)
empirical risk
(1)
regularization theory
(1)
sparse optimization
(1)
ridge regression
(1)
Papers
Learning with Gradient Descent and Weakly Convex Losses
AISTATS 2021
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel
NIPS 2021
Distributed Machine Learning with Sparse Heterogeneous Data
NIPS 2021
Asymptotics of Ridge(less) Regression under General Source Condition
AISTATS 2021
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent
JMLR 2020
Decentralised Learning with Random Features and Distributed Gradient Descent
ICML 2020
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
NIPS 2019