Jonathan How
7 papers · 2014–2021 · 3 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (24) π Conference Polyglot Β· Bronze
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Keyword Pioneer
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Trend Setter
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Conference Pioneer
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Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(7)
Artificial Intelligence
(4)
Optimization & Theory
(4)
Reinforcement Learning
(3)
Learning Types
(3)
Methods
(3)
Robotics
(2)
Bayesian & Probabilistic
(2)
Capabilities
(2)
Core AI
(2)
Learning Paradigms
(2)
Computer Science
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Applications
(1)
Keywords
gaussian process
(2)
sample efficiency
(1)
online learning
(1)
probabilistic modeling
(1)
policy optimization
(1)
real-time control
(1)
policy gradient
(1)
risk-aware planning
(1)
model fusion
(1)
importance sampling
(1)
policy search
(1)
partially observable markov decision process
(1)
model-based reinforcement learning
(1)
budgeted optimization
(1)
landmark selection
(1)
submodular maximization
(1)
approximation algorithm
(1)
information gain
(1)
model-free reinforcement learning
(1)
non-stationary environment
(1)
Papers
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
ICML 2021
Collision Probabilities for Continuous-Time Systems Without Sampling
RSS 2020
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
AAAI 2019
Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection
RSS 2018
Policy Search for Multi-Robot Coordination under Uncertainty
RSS 2015
Two-Stage Focused Inference for Resource-Constrained Collision-Free Navigation
RSS 2015
Sample Efficient Reinforcement Learning with Gaussian Processes
ICML 2014