Andrew Patterson
10 papers · 2018–2024 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (21)
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Keyword Collector
(52)
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Trend Setter
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Century Club Β· Bronze
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Unstoppable Β· Bronze
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Conference Pioneer
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Research topics
Machine Learning
(8)
Reinforcement Learning
(4)
Methods
(4)
Optimization & Theory
(3)
Artificial Intelligence
(2)
Robotics
(2)
Applications
(2)
Core Methods
(2)
Learning Types
(2)
Deep Learning
(1)
Architectures
(1)
Bayesian & Probabilistic Β· Machine Learning
(1)
Bayesian & Probabilistic Β· Artificial Intelligence
(1)
Capabilities
(1)
Core AI
(1)
Keywords
temporal difference learning
(3)
reinforcement learning
(2)
off-policy learning
(2)
bayesian learning
(1)
hypothesis testing
(1)
policy gradient
(1)
path planning
(1)
tensor decomposition
(1)
stability analysis
(1)
gaussian process
(1)
value function approximation
(1)
bellman equation
(1)
gaussian process regression
(1)
contraction theory
(1)
model-based reinforcement learning
(1)
function approximation
(1)
experimental design
(1)
state abstraction
(1)
continuous state
(1)
motion planning
(1)
Papers
Empirical Design in Reinforcement Learning
JMLR 2024
A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning
JMLR 2022
A Temporal-Difference Approach to Policy Gradient Estimation
ICML 2022
Contraction L1-Adaptive Control using Gaussian Processes
L4DC 2021
Gradient Temporal-Difference Learning with Regularized Corrections
ICML 2020
L1-GP: L1 Adaptive Control with Bayesian Learning
L4DC 2020
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization
NeurIPS 2019
Proximity Queries for Absolutely Continuous Parametric Curves
RSS 2019
Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains
IJCAI 2018
Supervised autoencoders: Improving generalization performance with unsupervised regularizers
NeurIPS 2018