Research
研究
研究業績
カテゴリー
研究領域
年
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“ADOPT: Modified Adam Can Converge with Any β2 with the Optimal Rate”
Shohei Taniguchi, Keno Harada, Gouki Minegishi, Yuta Oshima, Seong Cheol Jeong, Go Nagahara, Tomoshi Iiyama, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo
Advances in Neural Information Processing Systems 37 (NeurIPS 2024)
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ガウス過程潜在変数モデルとニューラルネットワークの統合によるマルチエージェント記号創発と潜在表現学習
中村友昭, 鈴木雅大, 谷口彰, 谷口忠大
日本ロボット学会誌（レター）, (2024)
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HAWK-Net: Hierarchical Attention Weighted Top-K Network for Megapixel Image Classification
Hitoshi Nakanishi, Masahiro Suzuki, Yutaka Matsuo
IPSJ, (2023).
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Fixing the train-test objective discrepancy: Iterative Image Inpainting for Unsupervised Anomaly Detection
Hitoshi Nakanishi, Masahiro Suzuki, Yutaka Matuo.
J-Stage in August Vol.30, (2022).
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Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization
Yusuke Iwasawa, and Yutaka Matsuo.
Advances in Neural Information Processing Systems 2021 (NeurIPS2021, Spotlight). December 2021.
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Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning
Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, and Shixiang Shane Gu.
Advances in Neural Information Processing Systems 2021 (NeurIPS2021). December 2021.
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“Information-theoretic regularization for learning global features by sequential VAE”
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
Mach Learn (2021)
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深層ニューラルネットワークによるクラスと幾何変換の同時分類確率を利用した分布外検知
岡本弘野, 鈴木雅大, 松尾豊
情報処理学会論文誌, Vol.62, No.7, pp.1382-1392 (2021)
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深層ニューラルネットワークの中間層出力を利用した半教師あり分布外検知
岡本弘野, 鈴木雅大, 松尾豊
情報処理学会論文誌, Vol.62, No.4, pp.1142-1151 (2021)
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Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, and Shixiang Shane Gu
International Conference on Machine Learning 2021 (ICML2021).