
Near optimal sample complexity for matrix and tensor normal models via geodesic convexity
The matrix normal model, the family of Gaussian matrixvariate distribut...
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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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NoRegret Reinforcement Learning with Value Function Approximation: a Kernel Embedding Approach
We consider the regret minimisation problem in reinforcement learning (R...
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Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
We establish a general form of explicit, inputdependent, measurevalued...
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Heteroscedastic Bayesian Optimisation for Stochastic Model Predictive Control
Model predictive control (MPC) has been successful in applications invol...
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DISCO: Double Likelihoodfree Inference Stochastic Control
Accurate simulation of complex physical systems enables the development,...
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Towards a theory of noncommutative optimization: geodesic first and second order methods for moment maps and polytopes
This paper initiates a systematic development of a theory of noncommuta...
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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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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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Bayesian optimisation under uncertain inputs
Bayesian optimisation (BO) has been a successful approach to optimise fu...
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Towards Optimal Depth Reductions for Syntactically Multilinear Circuits
We show that any nvariate polynomial computable by a syntactically mult...
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Recent progress on scaling algorithms and applications
Scaling problems have a rich and diverse history, and thereby have found...
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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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Operator Scaling via Geodesically Convex Optimization, Invariant Theory and Polynomial Identity Testing
We propose a new secondorder method for geodesically convex optimizatio...
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Learning to Race through Coordinate Descent Bayesian Optimisation
In the automation of many kinds of processes, the observable outcome can...
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Alternating minimization, scaling algorithms, and the nullcone problem from invariant theory
Alternating minimization heuristics seek to solve a (difficult) global o...
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Barriers for Rank Methods in Arithmetic Complexity
Arithmetic complexity is considered simpler to understand than Boolean c...
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Bayesian Optimisation for Safe Navigation under Localisation Uncertainty
In outdoor environments, mobile robots are required to navigate through ...
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Rafael Oliveira
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