Dominic Richards
7 papers · 2019–2021 · 4 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Bronze
🌉
Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(16)
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Hot Topic Early Bird
Venues
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Research topics
Machine Learning
(7)
Optimization & Theory · Machine Learning
(7)
Mathematics & Optimization
(3)
Artificial Intelligence
(2)
Core Methods
(2)
Learning Paradigms · Artificial Intelligence
(2)
Optimization
(2)
Deep Learning
(1)
Learning Paradigms · Machine Learning
(1)
Learning Types
(1)
Optimization & Theory · Deep Learning
(1)
Statistics
(1)
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)
multi-agent learning
(1)
generalization error
(1)
signal-to-noise ratio
(1)
kernel regression
(1)
excess risk
(1)
graph topology
(1)
nonparametric regression
(1)
empirical risk
(1)
regularization theory
(1)
sparse optimization
(1)
ridge regression
(1)
Papers
Asymptotics of Ridge(less) Regression under General Source Condition
AISTATS 2021
Distributed Machine Learning with Sparse Heterogeneous Data
NeurIPS 2021
Learning with Gradient Descent and Weakly Convex Losses
AISTATS 2021
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel
NeurIPS 2021
Decentralised Learning with Random Features and Distributed Gradient Descent
ICML 2020
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent
JMLR 2020
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
NeurIPS 2019