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08/08/2023
Path Signatures for Diversity in Probabilistic Trajectory Optimisation
Motion planning can be cast as a trajectory optimisation problem where a...
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09/22/2022
Batch Bayesian optimisation via density-ratio estimation with guarantees
Bayesian optimisation (BO) algorithms have shown remarkable success in a...
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03/13/2022
Adaptive Model Predictive Control by Learning Classifiers
Stochastic model predictive control has been a successful and robust con...
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03/10/2022
Robust Radical Sylvester-Gallai Theorem for Quadratics
We prove a robust generalization of a Sylvester-Gallai type theorem for ...
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03/01/2022
Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty
We propose an adaptive optimisation approach for tuning stochastic model...
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10/14/2021
Near optimal sample complexity for matrix and tensor normal models via geodesic convexity
The matrix normal model, the family of Gaussian matrix-variate distribut...
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03/23/2021
Dual Online Stein Variational Inference for Control and Dynamics
Model predictive control (MPC) schemes have a proven track record for de...
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11/16/2020
No-Regret Reinforcement Learning with Value Function Approximation: a Kernel Embedding Approach
We consider the regret minimisation problem in reinforcement learning (R...
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10/09/2020
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
We establish a general form of explicit, input-dependent, measure-valued...
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10/01/2020
Heteroscedastic Bayesian Optimisation for Stochastic Model Predictive Control
Model predictive control (MPC) has been successful in applications invol...
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02/18/2020
DISCO: Double Likelihood-free Inference Stochastic Control
Accurate simulation of complex physical systems enables the development,...
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10/27/2019
Towards a theory of non-commutative optimization: geodesic first and second order methods for moment maps and polytopes
This paper initiates a systematic development of a theory of non-commuta...
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10/02/2019
Search problems in algebraic complexity, GCT, and hardness of generator for invariant rings
We consider the problem of outputting succinct encodings of lists of gen...
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04/08/2019
More barriers for rank methods, via a "numeric to symbolic" transfer
We prove new barrier results in arithmetic complexity theory, showing se...
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02/21/2019
Bayesian optimisation under uncertain inputs
Bayesian optimisation (BO) has been a successful approach to optimise fu...
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02/19/2019
Towards Optimal Depth Reductions for Syntactically Multilinear Circuits
We show that any n-variate polynomial computable by a syntactically mult...
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08/29/2018
Recent progress on scaling algorithms and applications
Scaling problems have a rich and diverse history, and thereby have found...
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04/12/2018
Efficient algorithms for tensor scaling, quantum marginals and moment polytopes
We present a polynomial time algorithm to approximately scale tensors of...
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04/03/2018
Operator Scaling via Geodesically Convex Optimization, Invariant Theory and Polynomial Identity Testing
We propose a new second-order method for geodesically convex optimizatio...
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02/17/2018
Learning to Race through Coordinate Descent Bayesian Optimisation
In the automation of many kinds of processes, the observable outcome can...
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11/21/2017
Alternating minimization, scaling algorithms, and the null-cone problem from invariant theory
Alternating minimization heuristics seek to solve a (difficult) global o...
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10/26/2017
Barriers for Rank Methods in Arithmetic Complexity
Arithmetic complexity is considered simpler to understand than Boolean c...
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09/07/2017