Satoshi Hayakawa
Address
Mathematical Institute
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
- Clarendon Scholarship
- Toyota Riken Overseas Scholarship
TAs:
- MT20: B8.1 Probability, Measure and Martingales
- HT20: B8.2 Continuous Martingales and Stochastic Calculus
- MT21: B4.1 Functional Analysis
- HT21: C8.4 Probabilistic Combinatorics
Applied probability in general: more specifically on discretization of probability measures, convex hulls of random vectors, and kernel / Bayesian quadratures
Quantum ridgelet transform: Winning lottery ticket of neural networks with quantum computation
Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda, ICML 2023
Sampling-based Nyström approximation and kernel quadrature
Satoshi Hayakawa, Harald Oberhauser, Terry Lyons, ICML 2023
Hypercontractivity meets random convex hulls: Analysis of randomized multivariate cubatures
Satoshi Hayakawa, Harald Oberhauser, Terry Lyons, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023
Convergence analysis of approximation formulas for analytic functions via duality for potential energy minimization
Satoshi Hayakawa, Ken'ichiro Tanaka, Japan Journal of Industrial and Applied Mathematics, 2023
Estimating the probability that a given vector is in the convex hull of a random sample
Satoshi Hayakawa, Terry Lyons, Harald Oberhauser, Probability Theory and Related Fields, 185, 705-746, 2023
Fast Bayesian inference with batch Bayesian quadrature via kernel recombination
Masaki Adachi*, Satoshi Hayakawa*, Martin Jørgensen, Harald Oberhauser, Michael A Osborne, NeurIPS 2022 (*equal contribution)
Positively weighted kernel quadrature via subsampling
Satoshi Hayakawa, Harald Oberhauser, Terry Lyons, NeurIPS 2022
Monte Carlo construction of cubature on Wiener space
Satoshi Hayakawa, Ken'ichiro Tanaka, Japan Journal of Industrial and Applied Mathematics, 39(2), 543-571, 2022
Monte Carlo cubature construction
Satoshi Hayakawa, Japan Journal of Industrial and Applied Mathematics, 38(2), 561-577, 2021
Error bounds of potential theoretic numerical integration formulas in weighted Hardy spaces
Satoshi Hayakawa, Ken'ichiro Tanaka, JSIAM Letters, 12, 21-24, 2020
On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces
Satoshi Hayakawa, Taiji Suzuki, Neural Networks, 123, 343-361, 2020