We are pleased to announce OMI Faculty, Students and Associates have had five full papers and several workshop papers accepted at one of the top Machine Learning conferences, ICML

(* indicates equal contribution and co-lead authorship and OMI members/associates are underlined)

Main Conference Papers

Ready Policy One: World Building Through Active Learning
Philip Ball*, Jack Parker-Holder*, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts
to appear in The International Conference on Machine Learning (ICML), 2020 (ArXiv

Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano*, Jack Parker-Holder*, Yunhao Tang*, Anna Choromanska, Krzysztof Choromanski, Michael I. Jordan
to appear in The International Conference on Machine Learning (ICML), 2020 (ArXiv)

Stochastic Flows and Geometric Optimization on the Orthogonal Group
Krzysztof Choromanski*, David Cheikhi*, Jared Davis*, Valerii Likhosherstov*, Achille Nazaret*, Achraf Bahamou*, Xingyou Song*, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani
to appear in The International Conference on Machine Learning (ICML), 2020 (ArXiv)

Bayesian Optimisation over Multiple Continuous and Categorical Inputs
Binxin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J Roberts
to appear in The International Conference on Machine Learning (ICML), 2020 (ArXiv)

Knowing The What But Not The Where in Bayesian Optimization
Vu Nguyen, Michael A Osborne 
to appear in The International Conference on Machine Learning (ICML), 2020 (ArXiv)

Workshop Papers

Samuel Kessler, Arnold Salas, Vincent Tan Weng Choon, Stefan Zohren and Stephen Roberts (2020).
Practical Bayesian Neural Networks via Adaptive Subgradient Optimization Methods.
ICML 2020 workshop on Uncertainty and Robustness in Deep Learning

Sam Kessler, Jack Parker-Holder, Philip Ball, Stefan Zohren and Stephen Roberts (2020).
UNCLEAR: A Straightforward Method for Continual Reinforcement Learning.
ICML 2020 Workshop on Continual Learning.

Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts (2020).
Effective Diversity in Population Based Reinforcement Learning.
LifelongML workshop, ICML.

Jack Parker-Holder, Vu Nguyen, Stephen Roberts (2020).
One-Shot Bayes Opt via Probabilistic Population Based Training.
7th ICML Workshop on Automated Machine Learning (AutoML)

V. Nguyen*, S. Schulze*, M. A. Osborne
Bayesian Optimisation for Iterative Learning
AutoML Workshop at International Conference on Machine Learning (ICML), 2020.

Jack Parker-Holder*, Cinjon Resnick, Luke Metz, Hengyuan Hu, Adam Lerer, Alistair HP Letcher , Alex Peysakhovich, Aldo Pacchiano, Jakob Foerster*
Ridge Riding: Finding diverse solutions by following eigenvectors of the Hessian.
Beyond First Order Methods in ML Systems, ICML 2020.

Robert Müller, Jack Parker-Holder, Aldo Pacchiano
Taming the Herd: Multi-Modal Meta-Learning with a Population of Agents
Lifelong ML Workshop, ICML 2020.

Martin Tegner (2020).
Online Learning for Distributed and Personal Recommendations.
2nd ICML Workshop on Human in the Loop Learning.