Tomoyuki Obuchi

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 26

Top Topics

Linear Regression

Top Venues

J. Mach. Learn. Res.

Publications

Kyoya Uemura, Tomoyuki Obuchi, Toshiyuki Tanaka
Sparse Modeling for Spectrometer Based on Band Measurement. IEEE Trans. Signal Process. 72 (2024)
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
On Model Selection Consistency of Lasso for High-Dimensional Ising Models. AISTATS (2023)
Fumito Tagashira, Tomoyuki Obuchi, Toshiyuki Tanaka
Sharp Asymptotics of Matrix Sketching for a Rank-One Spiked Model. ISIT (2021)
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
On Model Selection Consistency of Lasso for High-Dimensional Ising Models on Tree-like Graphs. CoRR (2021)
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A Statistical Mechanics Analysis. NeurIPS (2021)
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
-Regularized Linear Regression. CoRR (2021)
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
-Regularized Linear Estimator. CoRR (2020)
Kao Hayashi, Tomoyuki Obuchi, Yoshiyuki Kabashima
Perfect Reconstruction of Sparse Signals via Greedy Monte-Carlo Search. CoRR (2020)
Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima
Inferring Neuronal Couplings From Spiking Data Using a Systematic Procedure With a Statistical Criterion. Neural Comput. 32 (11) (2020)
Ayaka Sakata, Tomoyuki Obuchi
Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control. CoRR (2019)
Alia Abbara, Yoshiyuki Kabashima, Tomoyuki Obuchi, Yingying Xu
Learning performance in inverse Ising problems with sparse teacher couplings. CoRR (2019)
Tomoyuki Obuchi, Ayaka Sakata
Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration. CoRR (2019)
Tomoyuki Obuchi, Yoshiyuki Kabashima
Semi-Analytic Resampling in Lasso. J. Mach. Learn. Res. 20 (2019)
Muneki Yasuda, Tomoyuki Obuchi
Empirical Bayes Method for Boltzmann Machines. CoRR (2019)
Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima
Objective and efficient inference for couplings in neuronal networks. NeurIPS (2018)
Tatsuro Kawamoto, Masashi Tsubaki, Tomoyuki Obuchi
Mean-field theory of graph neural networks in graph partitioning. CoRR (2018)
Tomoyuki Obuchi, Yoshiyuki Kabashima
Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization. J. Mach. Learn. Res. 19 (2018)
Tatsuro Kawamoto, Masashi Tsubaki, Tomoyuki Obuchi
Mean-field theory of graph neural networks in graph partitioning. NeurIPS (2018)
Tomoyuki Obuchi, Yoshinori Nakanishi-Ohno, Masato Okada, Yoshiyuki Kabashima
Statistical mechanical analysis of sparse linear regression as a variable selection problem. CoRR (2018)
Tomoyuki Obuchi, Yoshiyuki Kabashima
Cross validation in LASSO and its acceleration. CoRR (2016)
Yoshiyuki Kabashima, Tomoyuki Obuchi, Makoto Uemura
Approximate cross-validation formula for Bayesian linear regression. CoRR (2016)
Yoshiyuki Kabashima, Tomoyuki Obuchi, Makoto Uemura
Approximate cross-validation formula for Bayesian linear regression. Allerton (2016)
Tomoyuki Obuchi, Yoshiyuki Kabashima
Sampling approach to sparse approximation problem: Determining degrees of freedom by simulated annealing. EUSIPCO (2016)
Tomoyuki Obuchi, Yoshiyuki Kabashima
Sparse approximation problem: how rapid simulated annealing succeeds and fails. CoRR (2016)
Tomoyuki Obuchi, Yoshiyuki Kabashima
Sampling approach to sparse approximation problem: determining degrees of freedom by simulated annealing. CoRR (2016)
Yoshinori Nakanishi-Ohno, Tomoyuki Obuchi, Masato Okada, Yoshiyuki Kabashima
Dimensionality reduction based on an overcomplete basis. CoRR (2015)
Tomoyuki Obuchi, Hirokazu Koma, Muneki Yasuda
Estimation of priors in natural images. CoRR (2014)
Tomoyuki Obuchi, Kazutaka Takahashi, Koujin Takeda
Statistical mechanical analysis of hierarchical random code ensemble in signal processing CoRR (2010)