Classification and clustering of information objects based on fuzzy neighborhood system. - Sadaaki Miyamoto; Yasunori Endo; Satoshi Hayakawa; Erina Kataoka (SMC, 2005)

A Fuzzy Neighborhood Model for Clustering, Classification, and Approximations. - Sadaaki Miyamoto; Satoshi Hayakawa (RSCTC, 2006)

Term Clustering in Texts Based on Fuzzy Neighborhoods and Kernel Functions. - Sadaaki Miyamoto; Satoshi Hayakawa; Yuichi Kawasaki (KES (2), 2007)

In vitro cytocompatibility of microspheres derived from chitosan-silicate hybrids. - Yuki Shirosaki; Kohei Okamoto; Satoshi Hayakawa; Akiyoshi Osaka (MHS, 2013)

Affecting market efficiency by increasing speed of order matching systems on financial exchanges - investigation using agent based model. - Takanobu Mizuta; Yoshito Noritake; Satoshi Hayakawa; Kiyoshi Izumi (SSCI, 2016)

Convergence analysis of approximation formulas for analytic functions via duality for potential energy minimization. - Satoshi Hayakawa; Ken'ichiro Tanaka (CoRR, 2019)

Monte-Carlo Cubature construction. - Satoshi Hayakawa (CoRR, 2020)

Monte Carlo construction of cubature on Wiener space. - Satoshi Hayakawa; Ken'ichiro Tanaka (CoRR, 2020)

Error bounds of potential theoretic numerical integration formulas in weighted Hardy spaces. - Satoshi Hayakawa; Ken'ichiro Tanaka (JSIAM Lett., 2020)

On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces. - Satoshi Hayakawa; Taiji Suzuki (Neural Networks, 2020)

Synthesis of Adaptive Gain Robust Controllers for Polytopic Uncertain Systems with Multiple Unknown Dead-Zone Inputs. - Satoshi Hayakawa; Takuya Nakagawa; Hidetoshi Oya; Yoshikatsu Hoshi (IECON, 2022)

Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. - Masaki Adachi; Satoshi Hayakawa; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (NeurIPS, 2022)

Positively Weighted Kernel Quadrature via Subsampling. - Satoshi Hayakawa; Harald Oberhauser; Terry J. Lyons (NeurIPS, 2022)

Hypercontractivity Meets Random Convex Hulls: Analysis of Randomized Multivariate Cubatures. - Satoshi Hayakawa; Harald Oberhauser; Terry J. Lyons (CoRR, 2022)

Sampling-based Nyström Approximation and Kernel Quadrature. - Satoshi Hayakawa; Harald Oberhauser; Terry J. Lyons (ICML, 2023)

Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation. - Hayata Yamasaki; Sathyawageeswar Subramanian; Satoshi Hayakawa; Sho Sonoda (ICML, 2023)

SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. - Masaki Adachi; Satoshi Hayakawa; Saad Hamid; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (CoRR, 2023)

Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. - Masaki Adachi; Satoshi Hayakawa; Xingchen Wan; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (CoRR, 2023)

Synthesis of adaptive gain robust model-following/tracking controllers for uncertain systems with multiple unknown dead-zone inputs via piecewise Lyapunov functions. - Satoshi Hayakawa; Takuya Nakagawa; Kazuma Hasegawa; Hidetoshi Oya; Yoshikatsu Hoshi (Int. J. Syst. Sci., 2023)

Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. - Masaki Adachi; Satoshi Hayakawa; Martin Jørgensen; Xingchen Wan; Vu Nguyen; Harald Oberhauser; Michael A. Osborne (AISTATS, 2024)

A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. - Masaki Adachi; Satoshi Hayakawa; Martin Jørgensen; Saad Hamid; Harald Oberhauser; Michael A. Osborne (CoRR, 2024)

Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models. - Yong-Hyun Park; Chieh-Hsin Lai; Satoshi Hayakawa; Yuhta Takida; Yuki Mitsufuji (CoRR, 2024)

Distillation of Discrete Diffusion through Dimensional Correlations. - Satoshi Hayakawa; Yuhta Takida; Masaaki Imaizumi; Hiromi Wakaki; Yuki Mitsufuji (CoRR, 2024)

Synthesis of adaptive gain robust model-following/tracking controllers for a class of uncertain systems via piecewise Lyapunov functions. - Satoshi Hayakawa; Takuya Nakagawa; Kazuma Hasegawa; Hidetoshi Oya; Yoshikatsu Hoshi (Int. J. Control, 2024)

Policy Gradient with Kernel Quadrature. - Satoshi Hayakawa; Tetsuro Morimura (Trans. Mach. Learn. Res., 2024)

Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models. - Yong-Hyun Park; Chieh-Hsin Lai; Satoshi Hayakawa; Yuhta Takida; Yuki Mitsufuji (ICLR, 2025)

Concept-TRAK: Understanding how diffusion models learn concepts through concept-level attribution. - Yong-Hyun Park; Chieh-Hsin Lai; Satoshi Hayakawa; Yuhta Takida; Naoki Murata; Wei-Hsiang Liao 001; Woosung Choi; Kin Wai Cheuk; Junghyun Koo; Yuki Mitsufuji (CoRR, 2025)