58 citations · 336 across the 38 of their papers we have counts for
39 papers
Assessing transfer entropy from biochemical data
Takuya Imaizumi, Nobuhisa Umeki, Ryo Yoshizawa +3
We address the problem of evaluating the transfer entropy (TE) produced by biochemical reactions from experimentally measured data. Although these reactions are generally non-linea…
On Model Selection Consistency of Lasso for High-Dimensional Ising Models
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
We theoretically analyze the model selection consistency of least absolute shrinkage and selection operator (Lasso), both with and without post-thresholding, for high-dimensional I…
Ising Model Selection Using -Regularized Linear Regression: A Statistical Mechanics Analysis
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
We theoretically analyze the typical learning performance of -regularized linear regression (-LinR) for Ising model selection using the replica method from statis…
Structure Learning in Inverse Ising Problems Using -Regularized Linear Estimator
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
The inference performance of the pseudolikelihood method is discussed in the framework of the inverse Ising problem when the -regularized (ridge) linear regression is adopt…
Reconstructing Sparse Signals via Greedy Monte-Carlo Search
Kao Hayashi, Tomoyuki Obuchi, Yoshiyuki Kabashima
We propose a Monte-Carlo-based method for reconstructing sparse signals in the formulation of sparse linear regression in a high-dimensional setting. The basic idea of this algorit…
Learning performance in inverse Ising problems with sparse teacher couplings
Alia Abbara, Yoshiyuki Kabashima, Tomoyuki Obuchi +1
We investigate the learning performance of the pseudolikelihood maximization method for inverse Ising problems. In the teacher-student scenario under the assumption that the teache…