Maximal margin labeling for multi-topic text categorization H Kazawa, T Izumitani, H Taira, E Maeda Advances in neural information processing systems 17, 2004 | 183 | 2004 |
Bayesian semi-supervised audio event transcription based on Markov Indian buffet process Y Ohishi, D Mochihashi, T Matsui, M Nakano, H Kameoka, T Izumitani, ... 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 37 | 2013 |
A background music detection method based on robust feature extraction T Izumitani, R Mukai, K Kashino 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 37 | 2008 |
A Robust Musical Audio Search Method Based on Diagonal Dynamic Programming Matching of Self-Similarity Matrices. T Izumitani, K Kashino ISMIR, 609-613, 2008 | 15 | 2008 |
Assigning gene ontology categories (go) to yeast genes using text-based supervised learning methods T Izumitani, H Taira, H Kazawa, E Maeda Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004 …, 2004 | 15 | 2004 |
NTT Communication Science Laboratories and National Institute of Informatics at TRECVID 2012 Instance Search and Multimedia Event Detection Tasks. M Murata, T Izumitani, H Nagano, R Mukai, K Kashino, ... TRECVID, 2012 | 8 | 2012 |
L1-Norm Gradient Penalty for Noise Reduction of Attribution Maps. K Kiritoshi, R Tanno, T Izumitani CVPR Workshops, 118-121, 2019 | 6 | 2019 |
Effective nonlinear feature selection method based on hsic lasso and with variational inference K Koyama, K Kiritoshi, T Okawachi, T Izumitani International Conference on Artificial Intelligence and Statistics, 10407-10421, 2022 | 5 | 2022 |
Estimating individual-level optimal causal interventions combining causal models and machine learning models K Kiritoshi, T Izumitani, K Koyama, T Okawachi, K Asahara, S Shimizu The KDD'21 Workshop on Causal Discovery, 55-77, 2021 | 5 | 2021 |
Capturing time-varying influence using an attribution map method for neural networks K Kiritoshi, K Ito, T Izumitani IJCAI Workshop on AI for Internet of Things (AI4IoT), 2018 | 4 | 2018 |
機械学習を用いた工場機器の故障予測 切通恵介, 泉谷知範 DEIM Forum, H2-1, 2017 | 4 | 2017 |
Frequency component restoration for music sounds using a Markov random field and maximum entropy learning T Izumitani, K Kashino 2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006 | 4 | 2006 |
Causal Discovery for Non-stationary Non-linear Time Series Data Using Just-In-Time Modeling D Fujiwara, K Koyama, K Kiritoshi, T Okawachi, T Izumitani, S Shimizu Conference on Causal Learning and Reasoning, 880-894, 2023 | 2 | 2023 |
A Musical Audio Search Method Based on Self-Similarity Features T Izumitani, K Kashino 2007 IEEE International Conference on Multimedia and Expo, 68-71, 2007 | 1 | 2007 |
最大マージン原理に基づく多重ラベリング学習 賀沢秀人, 泉谷知範, 平博順, 前田英作, 磯崎秀樹 電子情報通信学会論文誌 D 88 (11), 2246-2259, 2005 | 1 | 2005 |
最大マージン原理にもとづく多重トピック文書の自動分類 賀沢秀人, 泉谷知範, 平博順, 前田英作 情報処理学会研究報告自然言語処理 (NL) 2004 (93 (2004-NL-163)), 53-60, 2004 | 1 | 2004 |
Assigning Gene Ontology (GO) Codes to Yeast Genes using Text-based Super-vised Learning Methods T Izumitani Proc. of IEEE Bioinformatics Conference (CSB-2004), 2004 | 1 | 2004 |
Prospects of Continual Causality for Industrial Applications D Fujiwara, K Koyama, K Kiritoshi, T Okawachi, T Izumitani, S Shimizu AAAI Bridge Program on Continual Causality, 18-24, 2023 | | 2023 |
合成関数の回帰モデルにおけるバイアス縮小 plug-in 推定の提案 片島健博, 大川内智海, 島田健一郎, 泉谷知範 人工知能学会全国大会論文集 第 37 回 (2023), 4E2GS205-4E2GS205, 2023 | | 2023 |
カウント時系列データに対するゼロ過剰ポアソン Transformer モデル 木村大地, 泉谷知範 人工知能学会全国大会論文集 第 37 回 (2023), 1B3GS203-1B3GS203, 2023 | | 2023 |