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Kentaro Minami

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2020 – today

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2022
[c6]
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  - conf/bigdataconf/FujimotoNIM22
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  - https://dblp.org/rec/conf/bigdataconf/FujimotoNIM22
Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami:
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. Big Data 2022: 1238-1245
[c5]
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  - conf/icaif/LiuMI22
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Ziyin Liu, Kentaro Minami, Kentaro Imajo:
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction. ICAIF 2022: 273-281
[i6]
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  - journals/corr/abs-2201-13127
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Masahiro Kato, Masaaki Imaizumi, Kentaro Minami:
Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics. CoRR abs/2201.13127 (2022)
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  - journals/corr/abs-2210-17030
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Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami:
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. CoRR abs/2210.17030 (2022)
2021
[c4]
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  - conf/aaai/ImajoMIN21
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Kentaro Imajo, Kentaro Minami, Katsuya Ito, Kei Nakagawa:
Deep Portfolio Optimization via Distributional Prediction of Residual Factors. AAAI 2021: 213-222
[c3]
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  - conf/atal/ItoMIN21
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Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa:
Trader-Company Method: A Metaheuristics for Interpretable Stock Price Prediction. AAMAS 2021: 656-664
[i4]
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  - journals/corr/abs-2106-04114
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Ziyin Liu, Kentaro Minami, Kentaro Imajo:
What Data Augmentation Do We Need for Deep-Learning-Based Finance? CoRR abs/2106.04114 (2021)
[i3]
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  - journals/corr/abs-2111-07679
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Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal:
Contrastive Representation Learning with Trainable Augmentation Channel. CoRR abs/2111.07679 (2021)
2020
[j1]
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  - journals/ma/Minami20
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Kentaro Minami:
Degrees of freedom in submodular regularization: A computational perspective of Stein's unbiased risk estimate. J. Multivar. Anal. 175 (2020)
[c2]
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  - conf/iclr/ChuMF20
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Casey Chu, Kentaro Minami, Kenji Fukumizu:
Smoothness and Stability in GANs. ICLR 2020
[i2]
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  - journals/corr/abs-2002-04185
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Casey Chu, Kentaro Minami, Kenji Fukumizu:
Smoothness and Stability in GANs. CoRR abs/2002.04185 (2020)
[i1]
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  - journals/corr/abs-2004-01822
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Casey Chu, Kentaro Minami, Kenji Fukumizu:
The equivalence between Stein variational gradient descent and black-box variational inference. CoRR abs/2004.01822 (2020)

2010 – 2019

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2016
[c1]
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  - conf/nips/MinamiASN16
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Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa:
Differential Privacy without Sensitivity. NIPS 2016: 956-964

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