Tomoyuki Obuchi

36 papers A* 3A 1B 1Journal 29Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Graphical model for tensor factorization by sparse sampling. CoRR Angelo Giorgio Cavaliere, Riki Nagasawa, Shuta Yokoi, Tomoyuki Obuchi, Hajime Yoshino
2025	J	`jnl`	Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model. CoRR Chuang Ma, Tomoyuki Obuchi, Toshiyuki Tanaka
2025	J	`jnl`	Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing. CoRR Xiaosi Gu, Ayaka Sakata, Tomoyuki Obuchi
2025	J	`jnl`	Transfer Learning in ℓ Trans. Mach. Learn. Res. Koki Okajima, Tomoyuki Obuchi
2025	J	`jnl`	When resampling/reweighting improves feature learning in imbalanced classification? A toy-model study. Trans. Mach. Learn. Res. Tomoyuki Obuchi, Toshiyuki Tanaka
2024	J	`jnl`	Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm. CoRR Xiaosi Gu, Tomoyuki Obuchi
2024	J	`jnl`	Sparse Modeling for Spectrometer Based on Band Measurement. IEEE Trans. Signal Process. Kyoya Uemura, Tomoyuki Obuchi, Toshiyuki Tanaka
2024	J	`jnl`	Transfer Learning in ℓ CoRR Koki Okajima, Tomoyuki Obuchi
2024	J	`jnl`	When resampling/reweighting improves feature learning in imbalanced classification?: A toy-model study. CoRR Tomoyuki Obuchi, Toshiyuki Tanaka
2023	A	`conf`	On Model Selection Consistency of Lasso for High-Dimensional Ising Models. AISTATS Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
2021	A*	`conf`	Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A Statistical Mechanics Analysis. NeurIPS Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
2021	J	`jnl`	Ising Model Selection Using 𝓁 CoRR Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
2021	J	`jnl`	On Model Selection Consistency of Lasso for High-Dimensional Ising Models on Tree-like Graphs. CoRR Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
2021	B	`conf`	Sharp Asymptotics of Matrix Sketching for a Rank-One Spiked Model. ISIT Fumito Tagashira, Tomoyuki Obuchi, Toshiyuki Tanaka
2020	J	`jnl`	Inferring Neuronal Couplings From Spiking Data Using a Systematic Procedure With a Statistical Criterion. Neural Comput. Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima
2020	J	`jnl`	Perfect Reconstruction of Sparse Signals via Greedy Monte-Carlo Search. CoRR Kao Hayashi, Tomoyuki Obuchi, Yoshiyuki Kabashima
2020	J	`jnl`	Structure Learning in Inverse Ising Problems Using 𝓁 CoRR Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
2019	J	`jnl`	Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration. CoRR Tomoyuki Obuchi, Ayaka Sakata
2019	J	`jnl`	Empirical Bayes Method for Boltzmann Machines. CoRR Muneki Yasuda, Tomoyuki Obuchi
2019	J	`jnl`	Learning performance in inverse Ising problems with sparse teacher couplings. CoRR Alia Abbara, Yoshiyuki Kabashima, Tomoyuki Obuchi, Yingying Xu
2019	J	`jnl`	Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control. CoRR Ayaka Sakata, Tomoyuki Obuchi
2019	J	`jnl`	Semi-Analytic Resampling in Lasso. J. Mach. Learn. Res. Tomoyuki Obuchi, Yoshiyuki Kabashima
2018	J	`jnl`	Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization. J. Mach. Learn. Res. Tomoyuki Obuchi, Yoshiyuki Kabashima
2018	A*	`conf`	Mean-field theory of graph neural networks in graph partitioning. NeurIPS Tatsuro Kawamoto, Masashi Tsubaki, Tomoyuki Obuchi
2018	J	`jnl`	Mean-field theory of graph neural networks in graph partitioning. CoRR Tatsuro Kawamoto, Masashi Tsubaki, Tomoyuki Obuchi
2018	A*	`conf`	Objective and efficient inference for couplings in neuronal networks. NeurIPS Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima
2018	J	`jnl`	Statistical mechanical analysis of sparse linear regression as a variable selection problem. CoRR Tomoyuki Obuchi, Yoshinori Nakanishi-Ohno, Masato Okada, Yoshiyuki Kabashima
2016	—	`conf`	Approximate cross-validation formula for Bayesian linear regression. Allerton Yoshiyuki Kabashima, Tomoyuki Obuchi, Makoto Uemura
2016	J	`jnl`	Approximate cross-validation formula for Bayesian linear regression. CoRR Yoshiyuki Kabashima, Tomoyuki Obuchi, Makoto Uemura
2016	J	`jnl`	Cross validation in LASSO and its acceleration. CoRR Tomoyuki Obuchi, Yoshiyuki Kabashima
2016	—	`conf`	Sampling approach to sparse approximation problem: Determining degrees of freedom by simulated annealing. EUSIPCO Tomoyuki Obuchi, Yoshiyuki Kabashima
2016	J	`jnl`	Sampling approach to sparse approximation problem: determining degrees of freedom by simulated annealing. CoRR Tomoyuki Obuchi, Yoshiyuki Kabashima
2016	J	`jnl`	Sparse approximation problem: how rapid simulated annealing succeeds and fails. CoRR Tomoyuki Obuchi, Yoshiyuki Kabashima
2015	J	`jnl`	Dimensionality reduction based on an overcomplete basis. CoRR Yoshinori Nakanishi-Ohno, Tomoyuki Obuchi, Masato Okada, Yoshiyuki Kabashima
2014	J	`jnl`	Estimation of priors in natural images. CoRR Tomoyuki Obuchi, Hirokazu Koma, Muneki Yasuda
2010	J	`jnl`	Statistical mechanical analysis of hierarchical random code ensemble in signal processing CoRR Tomoyuki Obuchi, Kazutaka Takahashi, Koujin Takeda