5 citations · 6 across the 8 of their papers we have counts for
5 papers · 1 filter
No-Regret Gaussian Process Optimization of Time-Varying Functions
Eliabelle Mauduit, Eloïse Berthier, Andrea Simonetto
Sequential optimization of black-box functions from noisy evaluations has been widely studied, with Gaussian Process bandit algorithms such as GP-UCB guaranteeing no-regret in stat…
Time-varying Gaussian Process Bandit Optimization with Experts: no-regret in logarithmically-many side queries
Eliabelle Mauduit, Eloïse Berthier, Andrea Simonetto
We study a time-varying Bayesian optimization problem with bandit feedback, where the reward function belongs to a Reproducing Kernel Hilbert Space (RKHS). We approach the problem…
Sampled-Based Guided Quantum Walk: Non-variational quantum algorithm for combinatorial optimization
Ugo Nzongani, Dylan Laplace Mermoud, Giuseppe Di Molfetta +1
We introduce SamBa-GQW, a novel quantum algorithm for solving binary combinatorial optimization problems of arbitrary degree with no use of any classical optimizer. The algorithm i…
Variational quantum algorithms for permutation-based combinatorial problems: Optimal ansatz generation with applications to quadratic assignment problems and beyond
Dylan Laplace Mermoud, Andrea Simonetto, Sourour Elloumi
We present a quantum variational algorithm based on a novel circuit that generates all permutations that can be spanned by one- and two-qubits permutation gates. The construction o…
Non-unitary enhanced transfer efficiency in quantum walk search on complex networks
Ugo Nzongani, Andrea Simonetto, Giuseppe Di Molfetta
The task of finding an element in an unstructured database is known as spatial search and can be expressed as a quantum walk evolution on a graph. In this article, we modify the us…