19 citations · 29 across the 10 of their papers we have counts for
12 papers
Kernel-based guarantees for nonlinear parametric models in Bayesian optimization
Rafael Oliveira
Modern Bayesian optimization and adaptive sampling methods increasingly rely on nonlinear parametric models, yet theoretical guarantees for such models under adaptive data collecti…
Stein Random Feature Regression
Houston Warren, Rafael Oliveira, Fabio Ramos
In large-scale regression problems, random Fourier features (RFFs) have significantly enhanced the computational scalability and flexibility of Gaussian processes (GPs) by defining…
Path Signatures for Diversity in Probabilistic Trajectory Optimisation
Lucas Barcelos, Tin Lai, Rafael Oliveira +2
Motion planning can be cast as a trajectory optimisation problem where a cost is minimised as a function of the trajectory being generated. In complex environments with several obs…
Batch Bayesian optimisation via density-ratio estimation with guarantees
Rafael Oliveira, Louis Tiao, Fabio Ramos
Bayesian optimisation (BO) algorithms have shown remarkable success in applications involving expensive black-box functions. Traditionally BO has been set as a sequential decision-…
Adaptive Model Predictive Control by Learning Classifiers
Rel Guzman, Rafael Oliveira, Fabio Ramos
Stochastic model predictive control has been a successful and robust control framework for many robotics tasks where the system dynamics model is slightly inaccurate or in the pres…
Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty
Rel Guzman, Rafael Oliveira, Fabio Ramos
We propose an adaptive optimisation approach for tuning stochastic model predictive control (MPC) hyper-parameters while jointly estimating probability distributions of the transit…
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning
Sayak Ray Chowdhury, Rafael Oliveira
We consider the regret minimization problem in reinforcement learning (RL) in the episodic setting. In many real-world RL environments, the state and action spaces are continuous o…
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
Anthony Tompkins, Rafael Oliveira, Fabio Ramos
We establish a general form of explicit, input-dependent, measure-valued warpings for learning nonstationary kernels. While stationary kernels are ubiquitous and simple to use, the…
DISCO: Double Likelihood-free Inference Stochastic Control
Lucas Barcelos, Rafael Oliveira, Rafael Possas +2
Accurate simulation of complex physical systems enables the development, testing, and certification of control strategies before they are deployed into the real systems. As simulat…
Bayesian optimisation under uncertain inputs
Rafael Oliveira, Lionel Ott, Fabio Ramos
Bayesian optimisation (BO) has been a successful approach to optimise functions which are expensive to evaluate and whose observations are noisy. Classical BO algorithms, however,…
Learning to Race through Coordinate Descent Bayesian Optimisation
Rafael Oliveira, Fernando H. M. Rocha, Lionel Ott +3
In the automation of many kinds of processes, the observable outcome can often be described as the combined effect of an entire sequence of actions, or controls, applied throughout…
Bayesian Optimisation for Safe Navigation under Localisation Uncertainty
Rafael Oliveira, Lionel Ott, Vitor Guizilini +1
In outdoor environments, mobile robots are required to navigate through terrain with varying characteristics, some of which might significantly affect the integrity of the platform…