publication
業績
- Publication
Published literature
PUBLISHED LITERATURE
Masahro Suzuki, Yutaka Matsuo: A survey of multimodal deep generative models, Advanced Robotics, 2022 |
Yuki Yamamoto, Keiichi Ochiai, Masahiro Suzuki, Yutaka Matsuo: Extracting Sentiment Indicators from Financial Reports by Using LSTM Model, IPSJ Transactions Digital Practices, 2022 |
Yutaka Matsuo, Two-story architecture of intelligence, Cognitive Studies: Bulletin of the Japanese Cognitive Science Society, 2022, Volume 29, Issue 1, Pages 36-46 |
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo. “Information-theoretic regularization for learning global features by sequential VAE”, Machine Learning, Vol 110, No.8 (2021). |
Jun Hozumi, Yusuke Iwasawa, Yutaka Matsuo: Time-Sequential Variational Autoencoders for Recommendation, Journal Article of The Japanese Society for Artificial Intelligence, VOL. 36，NO. 3 (2021) |
Hirono Okamoto, Masahiro Suzuki, Yutaka Matsuo: Out-of-distribution Detection Using Joint Probability between Class and Geometric Transformation, Transactions of Information Processing Society of Japan, VOL.62, NO.7, (2021) |
Hirono Okamoto, Masahiro Suzuki, Yutaka Matsuo: Semi-supervised Out-of-distribution Detection Using Output of Intermediate Layer in Deep Neural Networks, Transactions of Information Processing Society of Japan, VOL.62, NO.4, (2021) |
Tatsuya Matsushima, Naruya Kondo, Yusuke Iwasawa, Kaoru Nasuno, Yutaka Matsuo: Modeling Task Uncertainty for Safe Meta-imitation Learning, Frontiers in Robotics and AI, Vol. 7, pp.189, https://www.frontiersin.org/article/10.3389/frobt.2020.606361, 2020 |
Ikuko Eguchi Yairi, Hiroki Takahashi, Takumi Watanabe, Kouya Nagamine, Yusuke Fukushima, Yutaka Matsuo, Yusuke Iwasawa: Estimating Spatiotemporal Information from Behavioral Sensing Data of Wheelchair Users by Machine Learning Technologies. Information, Vol.10, No.3, 2019 |
Shizuma Kubo, Yusuke Iwasawa, Yutaka Matsuo: SwapGAN: Cloth-Region Aware Generative Adversarial Networks toword Virtual Try-On System, Transactions of Information Processing Society of Japan, 2019 |
Keiichi Ochiai, Daisuke Torii, Yusuke Fukazawa, Yutaka Matsuo: Fast and Diversity-aware Spatio-temporal Search for Twitter using Pre-search, Transactions of Information Processing Society of Japan, VOL. 60, NO.2, 2019 |
Masahiro Suzuki, Yutaka Matsuo: Semi-supervised Multimodal learning with Deep Generative Models, Transactions of Information Processing Society of Japan, VOL. 59, NO. 12, 2018 |
Hiromi Nakagawa, Kaoru Nasuno, Yusuke Iwasawa, Katsuya Uenoyama, Yutaka Matsuo: Generating Pseudo-Skill Tags by Extension of Deep Knowledge Tracing, Transactions of Information Processing Society of Japan, VOL.33, NO.3, PP.1-11, 2018 |
Koichiro Tamura, Katsuya Uenoyama, Shuhei Iitsuka, Yutaka Matsuo: Model for Evaluation of Stock Values by Ensemble Model Using Deep Learning, Transactions of the Japanese Society for Artificial Intelligence, VOL. 33，NO. 1, PP.1-11, 2017 |
Naoki Nonaka, Kotaro Nakayama, Yutaka Matsuo: Automobile Sales Prediction Using Features Extracted from Online Reviews that Contributes to Consumer Sentiment, Transactions of Information Processing Society of Japan Data base, VOL.10, NO.3, PP.16-25, 2017 |
Naoko Matsuda, Yutaka Matsuo: Impact of MBA on Entrepreneurial Success: Do Entrepreneurs Acquire Capacity through the Program or Does MBA Only Signal Gifted Talent and Experience?, Journal of Entrepreneurship & Organization Management, Vol. 6, No. 1, pp.1-7, 2017 |
Yusuke Iwasawa, Ikuko Yairi, Yutaka Matsuo: User-adversarial neutral networks, Transactions of Information Processing Society of Japan, VOL. 32，NO. 4，PP.1-12, 2017 |
Yusuke Iwasawa, Ikuko Yairi, Yutaka Matsuo: Semi-Supervised Distillation: Personalizing Deep Neural Networks in Activity Recognition using Inertial Sensors, Transactions of Information Processing Society of Japan, VOL. 32, NO. 3, PP.1-11, 2017 |
Yoshifumi Seki, Yoshinori Fukushima, Koji Yoshida, Yutaka Matsuo: Improving User Experience for Recommender System using Diversity, Journal of Natural Language Processing, VOL.24, NO.1, PP.95-115, 2017 |
Naoko Matsuda, Yutaka Matsuo: Governing Board Interlocks as an Indicator of IPO, Corporate Board: Role, Duties and Composition, Vol.12, Issue 3, pp.14-24, 2016 |
Masahiro Suzuki, haruhiko Sato, Satoshi Koyama, Masahito Kurihara, Yutaka Matsuo: Zero-shot Learning Based on the Observation Probability of Attributes, Journal of Natural Language Processing, VOL.57, NO.5, PP.1499-1513, 2016 |
Yusuke Iwasawa, Ikuko Yairi, Yutaka Matsuo: Combining Human Action Sensing of Wheelchair Users and Machine Learning for Autonomous Accessibility Data Collection, IEICE Transactions, Vol.99-D, No.4, pp.1153-1161, 2016 |
Kotaro Nakayama, Yutaka Matsuo: GeSdA―High Performane Deep Learning Implementation with Autoencoder Parallelization, Journal of Natural Language Processing Data Base (TOD), VOL.9, NO.2, PP.46-54, 2016 |
Keiichi Ochiai, Wataru Yamada, Yusuke Fukazawa, Yuu Kikuchi, Yutaka Matsuo: POI Official Account Classification Method Using Twitter Posts and Profile Information, Journal of Natural Language Processing Data Base (TOD), VOL.9, NO.2, PP.11-22, 2016 |
Shohei Osawa, Yutaka Matsuo: Rating Prediction for Software Developers by Integrating OSS Community and Crowd Sourcing, Transactions of the Japanese Society for Artificial Intelligence, VOL.31, NO.2, PP.1-10, 2016 |
Commentary
COMMENTARY
Yutaka Matsuo, Deep learning and artificial intelligence, Cognitive Studies: Bulletin of the Japanese Cognitive Science Society, 2021, Volume 28, Issue 2, Pages 299-307 |
Yutaka Matsuo, History and Trend of Artificial Intelligence Technologies, The Journal of the Institute of Electronics, Information and Communication Engineers, VOL.103, NO.5, |
Yutaka Matsuo, Potentials of Deep Learning for Services, Serviceology, VOL.4, NO.1, PP.10-15, 2017 |
Yutaka Matsuo, Expectations of Robot Field from Artificial Intelligence Field, Journal of the Robotics Society of Japan, VOL.35, NO.3, PP.174-179, 2017 |
Yutaka Matsuo, Artificial Intelligence and Ethics, Journal of Natural Language Processing, VOL.57, NO.10, PP.985-987, 2016 |
Yutaka Matsuo, Toyoaki Nishida, Koichi Hori, Hideaki Takeda, Satoshi Hase, Makoto Shiono, Hiromitsu Hattori, Arisa Ema, Katsue nagakura, Artificial Intelligence and Ethics, Transactions of the Japanese Society for Artificial Intelligence, VOL.31, NO.5, PP.635-641, 2016 |
Yutaka Matsuo, Deep Learning and Hard Problems in AI(<Special Issue>Deepening Machine Learning-Advanced Paradigm of Algorithms and their Applications), systems, control and information, VOL.60, NO.3, PP.92-98, 2016 |
International conference
INTERNATIONAL CONFERENCE
Hiroki Furuta, Yutaka Matsuo, and Shixiang Shane Gu. “Generalized Decision Transformer for Offline Hindsight Infomation Matching”, International Conference on Learning Representations 2022 (ICLR2022, Spotlight). April 2022. |
Shizuma Kazutoshi Shinoda, Yuki Takezawa, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo, Improving the Robustness to Variations of Objects and Instructions with a Neuro-Symbolic Approach for Interactive Instruction Following , Workshop on Novel Ideas in Learning-to-Learn through Interaction, EMNLP 2021, 2021. |
Hiroki Furuta, Yutaka Matsuo, and Shixiang Shane Gu. “Generalized Decision Transformer for Offline Hindsight Infomation Matching”, Deep Reinforcement Learning Workshop in Neural Information Processing Systems 2021 (NeurIPS2021). December 2021. |
Yusuke Iwasawa, and Yutaka Matsuo. “Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization”, Advances in Neural Information Processing Systems 2021 (NeurIPS2021, Spotlight). December 2021. |
Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, and Shixiang Shane Gu. “Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning”, Advances in Neural Information Processing Systems 2021 (NeurIPS2021). December 2021. |
Machel Reid, Junjie Hu, Graham Neubig and Yutaka Matsuo. “AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages”, The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021). November 2021. Association for Computational Linguistics. |
Machel Reid, Edison Marrese-Taylor and Yutaka Matsuo. “Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers”, Findings of The 2021 Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP 2021). November 2021. Association for Computational Linguistics. |
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, and Shixiang Shane Gu. “Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning”, International Conference on Machine Learning 2021 (ICML2021). July 2021. |
Machel Reid and Victor Zhong. “LEWIS: Levenshtein Editing for Unsupervised Text Style Transfer”, Findings of the Association for Computational Linguistics: The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). August 2021. |
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, and Shixiang Shane Gu. “Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning”, NERL 2021 Workshop on A Roadmap to Never-Ending Reinforcement Learning at International Conference on Learning Representations 2021 (ICLR2021) (Contributed Talk). May 2021. |
literary work
LITERARY WORK
ヤン・ルカン (著), 小川浩一 (翻訳), 松尾豊（監訳）, 「ディープラーニング 学習する機械 ヤン・ルカン、人工知能を語る」, 講談社, 2021 |
"Architects of Intelligence: the truth about AI from the people building it", Martin Ford, 2018 |
浅川 伸一, 江間 有沙, 工藤 郁子, 巣籠 悠輔, 瀬谷 啓介, 松井 孝之, 松尾 豊, 一般社団法人日本ディープラーニング協会 (監修)，「深層学習教科書 ディープラーニング G検定（ジェネラリスト） 公式テキスト」，翔泳社，2018 |
Deep Learning (Adaptive Computation and Machine Learning series), Ian Goodfellow, Yoshua Bengio and Aaron Courville, 2016 |
「ディープラーニングと人間拡張 (Deep Lerning and Human Expansion」，松尾 豊（分担執筆），オーグメンテッド・ヒューマン Augmented Human―AIと人体科学の融合による人機一体，究極のIFが創る未来，暦本 純一 他著，エヌ・ティー・エス，2018 |
松尾 豊, 中島 秀之, 西田 豊明, 溝口 理一郎, 長尾 真, 堀 浩一, 浅田 稔, 松原 仁, 武田 英明, 池上 高志, 山口 高平, 山川 宏, 栗原 聡, 「人工知能とは (What is Artificial Intelligence?)」, 松尾 豊 編, 近代科学社, 2016 |
「研究という営みを自省する (Self-reflection on the activity of research )」，松尾 豊（分担執筆），一人称研究のすすめ，諏訪 正樹・堀 浩一 編，3章，近代科学社，2015 |
「人工知能は人間を超えるか – ディープラーニングの先にあるもの (Will Artificial Intelligence Surpass Humans - Beyond Deep Learning)」, 松尾 豊, 角川, 2015 The book is only available in Japanese |
“Ranking Learning Entities on the Web by Integrating Network-Based Features”, Yingzi Jin, Yutaka Matsuo, Mitsuru Ishizuka, Mining and Analyzing Social Networks, Studies in Computational Intelligence, I-Hsien Ting, Hui-Ju Wu, Tien-Hwa Ho (Eds.), pp 107-123, 2010 |
Yutaka Matsuo, Junichiro Mori, Mitsuru Ishizuka: “Social Network Mining from the Web”, Data Mining Patterns: New Methods and Applications, Florent Masseglia ed., Idea Group Inc., 2007 |
"Word Weighting based on User's Browsing History"，Yutaka Matsuo, Adaptable And Adaptive Hypermedia Systems, Sherry Chen and George D. Magoulas (Ed.), chap. 10, Idea Group Publishing, 2005 |
"Prediction, Forecasting, and Chance Discovery", Yutaka Matsuo, Chance Discovery, Peter McBurney and Yukio Ohsawa (Ed.), chap. 3, Springer, 2003 |
「Small World：予兆発見を支援するネットワーク構造 (Small World: Network structure to support predictive detection)」，松尾 豊（分担執筆），チャンス発見の情報技術，大澤 幸生編，10章，東京電機出版，2003 The book is only available in Japanese |
「予測，予兆発見，そしてチャンス発見 (Prediction, Predictive Discovery, and Opportunity Discovery)」，松尾 豊（分担執筆），チャンス発見の情報技術，大澤 幸生編，2章，東京電機出版，2003 The book is only available in Japanese |