Katsuyuki Hagiwara

Publication Activity (10 Years)

Years Active: 1994-2023
Publications (10 Years): 10

Top Topics

Hard Thresholding

Forward Selection

Top Venues

IEICE Trans. Inf. Syst.

Publications

Katsuyuki Hagiwara
On Gradient Descent Training Under Data Augmentation with On-Line Noisy Copies. IEICE Trans. Inf. Syst. 106 (9) (2023)
Katsuyuki Hagiwara
On gradient descent training under data augmentation with on-line noisy copies. CoRR (2022)
Katsuyuki Hagiwara
Bridging between Soft and Hard Thresholding by Scaling. IEICE Trans. Inf. Syst. (9) (2022)
Katsuyuki Hagiwara
Bridging between soft and hard thresholding by scaling. CoRR (2021)
Katsuyuki Hagiwara
A Model Selection Criterion for LASSO Estimate with Scaling. ICONIP (2) (2019)
Katsuyuki Hagiwara
On an improvement of LASSO by scaling. CoRR (2018)
Katsuyuki Hagiwara
On a Fitting of a Heaviside Function by Deep ReLU Neural Networks. ICONIP (1) (2018)
Katsuyuki Hagiwara
A Scaling and Non-Negative Garrote in Soft-Thresholding. IEICE Trans. Inf. Syst. (11) (2017)
Katsuyuki Hagiwara
A Problem in Model Selection of LASSO and Introduction of Scaling. ICONIP (2) (2016)
Katsuyuki Hagiwara
On scaling of soft-thresholding estimator. Neurocomputing 194 (2016)
Katsuyuki Hagiwara
A Sparse Modeling Method Based on Reduction of Cost Function in Regularized Forward Selection. IEICE Trans. Inf. Syst. (1) (2014)
Katsuyuki Hagiwara
Least Angle Regression in Orthogonal Case. ICONIP (2) (2014)
Katsuyuki Hagiwara
Nonparametric Regression Method Based on Orthogonalization and Thresholding. IEICE Trans. Inf. Syst. (8) (2011)
Katsuyuki Hagiwara
On a training scheme based on orthogonalization and thresholding for a nonparametric regression problem. IJCNN (2010)
Katsuyuki Hagiwara
Orthogonalization and Thresholding Method for a Nonparametric Regression Problem. ICONIP (2) (2008)
Katsuyuki Hagiwara, Kenji Fukumizu
Relation between weight size and degree of over-fitting in neural network regression. Neural Networks 21 (1) (2008)
Katsuyuki Hagiwara
Orthogonal Shrinkage Methods for Nonparametric Regression under Gaussian Noise. ICONIP (1) (2007)
Katsuyuki Hagiwara, Hiroshi Ishitani
On the Expected Prediction Error of Orthogonal Regression with Variable Components. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (12) (2006)
Katsuyuki Hagiwara
Model Selection with Componentwise Shrinkage in Orthogonal Regression. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (7) (2003)
Katsuyuki Hagiwara
Regularization learning, early stopping and biased estimator. Neurocomputing 48 (1-4) (2002)
Katsuyuki Hagiwara
On the Problem in Model Selection of Neural Network Regression in Overrealizable Scenario. Neural Comput. 14 (8) (2002)
Katsuyuki Hagiwara, Taichi Hayasaka, Naohiro Toda, Shiro Usui, Kazuhiro Kuno
Upper bound of the expected training error of neural network regression for a Gaussian noise sequence. Neural Networks 14 (10) (2001)
Katsuyuki Hagiwara, Kazuhiro Kuno, Shiro Usui
On the Problem in Model Selection of Neural Network Regression in Overrealizable Scenario. IJCNN (6) (2000)
Katsuyuki Hagiwara, Kazuhiro Kuno
Regularization Learning and Early Stopping in Linear Networks. IJCNN (4) (2000)
Katsuyuki Hagiwara, Kazuhiro Kuno, Shiro Usui
Upper Bounds on the Expected Training Errors of Neural Networks Regressions for a Gaussian Noise. ICONIP (1998)
Taichi Hayasaka, Katsuyuki Hagiwara, Naohiro Toda, Shiro Usui
On the Model Selection for Linear Combination of Step-Type Basis Functions. ICONIP (1) (1997)
Shiro Usui, Yutaka Hirata, Katsuyuki Hagiwara, Naohiro Toda, Ichiro Akagi
An analysis of carp cerebellar eeg under the microgravitational environment. Systems and Computers in Japan 27 (3) (1996)
Qi Jia, Katsuyuki Hagiwara, Shiro Usui, Naohiro Toda
Analysis of the error back-propagation learning algorithms with gain. Systems and Computers in Japan 26 (6) (1995)
Qi Jia, Katsuyuki Hagiwara, Naohiro Toda, Shiro Usui
Equivalence relation between the back propagation learning process of an FNN and that of an FNNG. Neural Networks 7 (2) (1994)