Michael A. Osborne
22 papers · 2018–2024 · 5 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Bronze 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (31)
🔬
Deep Specialist
(15)
💎
Century Club · Bronze
⚡
Prolific Year · Productive
🗃️
Keyword Collector
(92)
🔥
Unstoppable · Bronze
Top co-authors
Research topics
Machine Learning
(20)
Optimization & Theory
(18)
Artificial Intelligence
(11)
Mathematics & Optimization
(8)
Bayesian & Probabilistic · Artificial Intelligence
(8)
Optimization
(8)
Bayesian & Probabilistic · Machine Learning
(6)
Core Methods
(5)
Learning Types
(3)
Deep Learning
(2)
Reinforcement Learning
(2)
Core AI
(2)
Learning Paradigms
(2)
Methods
(2)
Healthcare & Medicine
(1)
Keywords
bayesian optimization
(11)
gaussian process
(8)
acquisition function
(4)
hyperparameter optimization
(3)
bayesian optimisation
(3)
hyperparameter tuning
(3)
bayesian quadrature
(3)
model selection
(2)
environment variable
(2)
kernel methods
(2)
permutation invariance
(2)
robust policy
(2)
expected improvement
(2)
surrogate model
(2)
rare event
(2)
kernel design
(1)
optimal transport
(1)
variational inference
(1)
embedding learning
(1)
uncertainty quantification
(1)
Papers
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach
AISTATS 2024
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
NeurIPS 2024
Looping in the Human: Collaborative and Explainable Bayesian Optimization
AISTATS 2024
Principled Bayesian Optimization in Collaboration with Human Experts
NeurIPS 2024
Marginalising over Stationary Kernels with Bayesian Quadrature
AISTATS 2022
Robust Multi-Objective Bayesian Optimization Under Input Noise
ICML 2022
Universal Approximation of Functions on Sets
JMLR 2022
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
ICML 2021
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
ICML 2021
Bayesian Optimisation over Multiple Continuous and Categorical Inputs
ICML 2020
Distributionally Ambiguous Optimization for Batch Bayesian Optimization
JMLR 2020
Knowing The What But Not The Where in Bayesian Optimization
ICML 2020
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems
AAAI 2020
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
AISTATS 2020
Robust Reinforcement Learning with Bayesian Optimisation and Quadrature
JMLR 2020
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs
ICML 2019
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
ICML 2019
Automated Model Selection with Bayesian Quadrature
ICML 2019
Fingerprint Policy Optimisation for Robust Reinforcement Learning
ICML 2019
On the Limitations of Representing Functions on Sets
ICML 2019
Fast Information-theoretic Bayesian Optimisation
ICML 2018
Optimization, fast and slow: optimally switching between local and Bayesian optimization
ICML 2018