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06/16/2023
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization
This paper introduces a modular framework for Mixed-variable and Combina...
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05/16/2023
Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions
Reinforcement learning (RL) exhibits impressive performance when managin...
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01/30/2023
Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?
Learning decompositions of expensive-to-evaluate black-box functions pro...
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01/29/2023
Contextual Causal Bayesian Optimisation
Causal Bayesian optimisation (CaBO) combines causality with Bayesian opt...
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06/06/2022
Enhancing Safe Exploration Using Safety State Augmentation
Safe exploration is a challenging and important problem in model-free re...
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02/14/2022
SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation
Satisfying safety constraints almost surely (or with probability one) ca...
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02/14/2022
Reinforcement Learning in Presence of Discrete Markovian Context Evolution
We consider a context-dependent Reinforcement Learning (RL) setting, whi...
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01/24/2022
Learning Geometric Constraints in Task and Motion Planning
Searching for bindings of geometric parameters in task and motion planni...
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11/11/2021
BOiLS: Bayesian Optimisation for Logic Synthesis
Optimising the quality-of-results (QoR) of circuits during logic synthes...
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07/13/2021
Efficient and Reactive Planning for High Speed Robot Air Hockey
Highly dynamic robotic tasks require high-speed and reactive robots. The...
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07/06/2021
Implicit Variational Conditional Sampling with Normalizing Flows
We present a method for conditional sampling with normalizing flows when...
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06/07/2021
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning
We introduce a method based on deep metric learning to perform Bayesian ...
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03/13/2021
Online Double Oracle
Solving strategic games with huge action space is a critical yet under-e...
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12/15/2020
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?
Bayesian optimisation presents a sample-efficient methodology for global...
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12/07/2020
HEBO: Heteroscedastic Evolutionary Bayesian Optimisation
We introduce HEBO: Heteroscedastic Evolutionary Bayesian Optimisation th...
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02/10/2020
Compositional ADAM: An Adaptive Compositional Solver
In this paper, we present C-ADAM, the first adaptive solver for composit...
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10/18/2019
Multi-View Reinforcement Learning
This paper is concerned with multi-view reinforcement learning (MVRL), w...
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10/09/2019
Derivative-Free Order-Robust Optimisation
In this paper, we formalise order-robust optimisation as an instance of ...
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09/25/2019
α^α-Rank: Practically Scaling α-Rank through Stochastic Optimisation
Recently, α-Rank, a graph-based algorithm, has been proposed as a soluti...
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09/25/2019
α^α-Rank: Scalable Multi-agent Evaluation through Evolution
Although challenging, strategy profile evaluation in large connected lea...
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07/30/2019
Wasserstein Robust Reinforcement Learning
Reinforcement learning algorithms, though successful, tend to over-fit t...
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09/06/2018
Model-Based Stabilisation of Deep Reinforcement Learning
Though successful in high-dimensional domains, deep reinforcement learni...
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02/19/2018
Learning High-level Representations from Demonstrations
Hierarchical learning (HL) is key to solving complex sequential decision...
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02/09/2018
Balancing Two-Player Stochastic Games with Soft Q-Learning
Within the context of video games the notion of perfectly rational agent...
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08/06/2017
An Information-Theoretic Optimality Principle for Deep Reinforcement Learning
In this paper, we methodologically address the problem of cumulative rew...
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04/20/2016
