68 citations · 206 across the 14 of their papers we have counts for
5 papers · 1 filter
Linearly-involved Moreau-Enhanced-over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression
Masahiro Yukawa, Hiroyuki Kaneko, Kyohei Suzuki +1
We present an efficient mathematical framework based on the linearly-involved Moreau-enhanced-over-subspace (LiMES) model. Two concrete applications are considered: sparse modeling…
Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields
Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez +1
This paper presents a convex-analytic framework to learn sparse graphs from data. While our problem formulation is inspired by an extension of the graphical lasso using the so-call…
Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to River State Estimation
Yuhei Kaneko, Shogo Muramatsu, Hiroyasu Yasuda +4
This work proposes convolutional-sparse-coded dynamic mode decomposition (CSC-DMD) by unifying extended dynamic mode decomposition (EDMD) and convolutional sparse coding. EDMD is a…
Distributed Adaptive Learning with Multiple Kernels in Diffusion Networks
Ban-Sok Shin, Masahiro Yukawa, Renato Luis Garrido Cavalcante +1
We propose an adaptive scheme for distributed learning of nonlinear functions by a network of nodes. The proposed algorithm consists of a local adaptation stage utilizing multiple…
Online Nonlinear Estimation via Iterative L2-Space Projections: Reproducing Kernel of Subspace
Motoya Ohnishi, Masahiro Yukawa
We propose a novel online learning paradigm for nonlinear-function estimation tasks based on the iterative projections in the L2 space with probability measure reflecting the stoch…