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Kentaro Minami
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2020 – today
- 2024
- [c11]Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano:
Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study. IIAI-AAI 2024: 329-336 - [c10]Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta:
A Multi-agent Market Model Can Explain the Impact of AI Traders in Financial Markets-A New Microfoundations of GARCH Model. PRIMA 2024: 97-113 - [i9]Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta:
A Multi-agent Market Model Can Explain the Impact of AI Traders in Financial Markets - A New Microfoundations of GARCH model. CoRR abs/2409.12516 (2024) - 2023
- [c9]Masahiro Kato, Masaaki Imaizumi, Kentaro Minami:
Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics. AISTATS 2023: 5271-5298 - [c8]Masanori Hirano
, Kentaro Minami, Kentaro Imajo:
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. ICAIF 2023: 19-26 - [c7]Masanori Hirano
Efficient Learning of Nested Deep Hedging using Multiple Options. IIAI-AAI 2023: 514-521 - [i8]Masanori Hirano
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. CoRR abs/2307.13217 (2023) - [i7]Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano:
Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study. CoRR abs/2311.07231 (2023) - 2022
- [c6]Yugo Fujimoto, Kei Nakagawa
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. IEEE Big Data 2022: 1238-1245 - [c5]Ziyin Liu, Kentaro Minami, Kentaro Imajo:
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction. ICAIF 2022: 273-281 - [i6]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) - [i5]Yugo Fujimoto, Kei Nakagawa
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. CoRR abs/2210.17030 (2022) - 2021
- [c4]Kentaro Imajo, Kentaro Minami, Katsuya Ito, Kei Nakagawa:
Deep Portfolio Optimization via Distributional Prediction of Residual Factors. AAAI 2021: 213-222 - [c3]Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa:
Trader-Company Method: A Metaheuristics for Interpretable Stock Price Prediction. AAMAS 2021: 656-664 - [i4]Ziyin Liu, Kentaro Minami, Kentaro Imajo:
What Data Augmentation Do We Need for Deep-Learning-Based Finance? CoRR abs/2106.04114 (2021) - [i3]Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal:
Contrastive Representation Learning with Trainable Augmentation Channel. CoRR abs/2111.07679 (2021) - 2020
- [j1]Kentaro Minami:
Degrees of freedom in submodular regularization: A computational perspective of Stein's unbiased risk estimate. J. Multivar. Anal. 175 (2020) - [c2]Casey Chu, Kentaro Minami, Kenji Fukumizu:
Smoothness and Stability in GANs. ICLR 2020 - [i2]Casey Chu, Kentaro Minami, Kenji Fukumizu:
Smoothness and Stability in GANs. CoRR abs/2002.04185 (2020) - [i1]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
- 2016
- [c1]Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa:
Differential Privacy without Sensitivity. NIPS 2016: 956-964
Coauthor Index
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