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20182026
most citedCompressed sensing radar detectors under the row-orthogonal design model: a statistical mechanics perspective

8 citations · 12 across the 6 of their papers we have counts for

collaborators

10 papers

cond-mat.stat-mech2026

Dynamical Regimes of Discrete Diffusion Models

Tomoei Takahashi, Takashi Takahashi, Yoshiyuki Kabashima

Diffusion models generate high-dimensional data such as images by learning a process that gradually removes noise from corrupted data. Recent studies have shown that the backward d…

eess.SP2023★ 1 cited

Compressed Sensing Radar Detectors based on Weighted LASSO

Siqi Na, Yoshiyuki Kabashima, Takashi Takahashi +3

The compressed sensing (CS) model can represent the signal recovery process of a large number of radar systems. The detection problem of such radar systems has been studied in many…

cond-mat.dis-nn2023

Average case analysis of Lasso under ultra-sparse conditions

Koki Okajima, Xiangming Meng, Takashi Takahashi +1

We analyze the performance of the least absolute shrinkage and selection operator (Lasso) for the linear model when the number of regressors grows larger keeping the true suppo…

cs.IT2023★ 2 cited

Role of Bootstrap Averaging in Generalized Approximate Message Passing

Takashi Takahashi

Generalized approximate message passing (GAMP) is a computationally efficient algorithm for estimating an unknown signal from a random linear measurement $y= X…

eess.SP2022★ 8 cited

Compressed sensing radar detectors under the row-orthogonal design model: a statistical mechanics perspective

Siqi Na, Tianyao Huang, Yimin Liu +3

Compressed sensing (CS) model of complex-valued data can represent the signal recovery process of a large amount types of radar systems, especially when the measurement matrix is r…

math.OC2022

Statistical mechanics analysis of general multi-dimensional knapsack problems

Yuta Nakamura, Takashi Takahashi, Yoshiyuki Kabashima

Knapsack problem (KP) is a representative combinatorial optimization problem that aims to maximize the total profit by selecting a subset of items under given constraints on the to…