Takafumi Kanamori - Publications, H-index & Citations

Takafumi Kanamori

Institute of Science Tokyo

27H指数

172论文数

3.1K被引数

收录论文 20

发表时间

Noiseless Diffusion-GAN: Scaling-based data augmentation for generative models 无噪声扩散生成对抗网络：基于放缩的数据增强方法用于生成模型

Neural Networks

IF6.3

2025-12-11

OAAI

Yoshitaka Koike; Takumi Nakagawa; Hiroki Waida; Takafumi Kanamori

Ultra-Fast NAS Based on Normalized Generalization Error with Random NTK 基于归一化泛化误差和随机NTK的超快神经架构搜索

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS

IF0.8

2025-10-01

OAAI

Wakayama, Keigo; Kanamori, Takafumi

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain

NEURAL NETWORKS

IF6.3

2025-03-01

PREAI

Yang, Lan; Qiao, Chen; Kanamori, Takafumi; Calhoun, Vince D.; Stephen, Julia M.; Wilson, Tony W.; Wang, Yu-Ping

Denoising cosine similarity: A theory-driven approach for efficient representation learning 去噪余弦相似性: 一种理论驱动的高效表示学习方法

NEURAL NETWORKS

IF6.3

2024-01-01

OAAI

Nakagawa, Takumi; Sanada, Yutaro; Waida, Hiroki; Zhang, Yuhui; Wada, Yuichiro; Takanashi, Kosaku; Yamada, Tomonori; Kanamori, Takafumi

Learning domain invariant representations by joint Wasserstein distance minimization

NEURAL NETWORKS

IF6.3

2023-10-01

OAAI

Andeol, Leo; Kawakami, Yusei; Wada, Yuichiro; Kanamori, Takafumi; Mueller, Klaus-Robert; Montavon, Gregoire

Uncertainty propagation for dropout-based Bayesian neural networks

NEURAL NETWORKS

IF6.3

2021-12-01

OAAI

Mae, Yuki; Kumagai, Wataru; Kanamori, Takafumi

Risk bound of transfer learning using parametric feature mapping and its application to sparse coding

MACHINE LEARNING

IF2.9

2019-05-20

OAAI

Kumagai, Wataru; Kanamori, Takafumi

Graph-based composite local Bregman divergences on discrete sample spaces

NEURAL NETWORKS

IF6.3

2017-11-01

OAAI

Kanamori, Takafumi; Takenouchi, Takashi

Robustness of learning algorithms using hinge loss with outlier indicators

NEURAL NETWORKS

IF6.3

2017-10-01

PREAI

Kanamori, Takafumi; Fujiwara, Shuhei; Takeda, Akiko

Using financial risk measures for analyzing generalization performance of machine learning models

NEURAL NETWORKS

IF6.3

2014-09-01

PREAI

Takeda, Akiko; Kanamori, Takafumi

Statistical models and learning algorithms for ordinal regression problems 有序回归问题的统计模型和学习算法

INFORMATION FUSION

IF15.5

2013-04-01

PREAI

Kanamori, Takafumi

Improving Logitboost with prior knowledge

INFORMATION FUSION

IF15.5

2013-04-01

PREAI

Kanamori, Takafumi; Takenouchi, Takashi

Semi-supervised learning with density-ratio estimation

MACHINE LEARNING

IF2.9

2013-02-09

OAAI

Kawakita, Masanori; Kanamori, Takafumi

Computational complexity of kernel-based density-ratio estimation: a condition number analysis

MACHINE LEARNING

IF2.9

2012-12-12

OAAI

Kanamori, Takafumi; Suzuki, Taiji; Sugiyama, Masashi

Statistical analysis of kernel-based least-squares density-ratio estimation

MACHINE LEARNING

IF2.9

2011-11-01

OAAI

Kanamori, Takafumi; Suzuki, Taiji; Sugiyama, Masashi

Least-squares two-sample test

NEURAL NETWORKS

IF6.3

2011-09-01

PREAI

Sugiyama, Masashi; Suzuki, Taiji; Itoh, Yuta; Kanamori, Takafumi; Kimura, Manabu

Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search

NEURAL NETWORKS

IF6.3

2011-03-01

PREAI

Sugiyama, Masashi; Yamada, Makoto; von Buenau, Paul; Suzuki, Taiji; Kanamori, Takafumi; Kawanabe, Motoaki

Deformation of log-likelihood loss function for multiclass boosting

NEURAL NETWORKS

IF6.3

2010-09-01

PREAI

Kanamori, Takafumi

A robust approach based on conditional value-at-risk measure to statistical learning problems

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

IF6

2009-10-01

PREAI

Takeda, Akiko; Kanamori, Takafumi

Pool-based active learning with optimal sampling distribution and its information geometrical interpretation

NEUROCOMPUTING

IF6.5

2007-12-01

PREAI

Kanamori, Takafumi

研究方向