Kentaro Minami

21 papers A* 2A 2B 2Journal 10Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A Multi-agent Market Model Can Explain the Impact of AI Traders in Financial Markets - A New Microfoundations of GARCH model. CoRR Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta
2024	B	`conf`	A Multi-agent Market Model Can Explain the Impact of AI Traders in Financial Markets-A New Microfoundations of GARCH Model. PRIMA Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta
2024	—	`conf`	Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study. IIAI-AAI Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano
2023	—	`conf`	Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. ICAIF Masanori Hirano, Kentaro Minami, Kentaro Imajo
2023	J	`jnl`	Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. CoRR Masanori Hirano, Kentaro Minami, Kentaro Imajo
2023	—	`conf`	Efficient Learning of Nested Deep Hedging using Multiple Options. IIAI-AAI Masanori Hirano, Kentaro Imajo, Kentaro Minami, Takuya Shimada
2023	J	`jnl`	Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study. CoRR Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano
2023	A	`conf`	Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics. AISTATS Masahiro Kato, Masaaki Imaizumi, Kentaro Minami
2022	—	`conf`	Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction. ICAIF Liu Ziyin, Kentaro Minami, Kentaro Imajo
2022	B	`conf`	Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. IEEE Big Data Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami
2022	J	`jnl`	Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. CoRR Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami
2022	J	`jnl`	Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics. CoRR Masahiro Kato, Masaaki Imaizumi, Kentaro Minami
2021	J	`jnl`	Contrastive Representation Learning with Trainable Augmentation Channel. CoRR Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal
2021	A*	`conf`	Deep Portfolio Optimization via Distributional Prediction of Residual Factors. AAAI Kentaro Imajo, Kentaro Minami, Katsuya Ito, Kei Nakagawa
2021	A	`conf`	Trader-Company Method: A Metaheuristics for Interpretable Stock Price Prediction. AAMAS Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa
2021	J	`jnl`	What Data Augmentation Do We Need for Deep-Learning-Based Finance? CoRR Liu Ziyin, Kentaro Minami, Kentaro Imajo
2020	J	`jnl`	Degrees of freedom in submodular regularization: A computational perspective of Stein's unbiased risk estimate. J. Multivar. Anal. Kentaro Minami
2020	A*	`conf`	Smoothness and Stability in GANs. ICLR Casey Chu, Kentaro Minami, Kenji Fukumizu
2020	J	`jnl`	Smoothness and Stability in GANs. CoRR Casey Chu, Kentaro Minami, Kenji Fukumizu
2020	J	`jnl`	The equivalence between Stein variational gradient descent and black-box variational inference. CoRR Casey Chu, Kentaro Minami, Kenji Fukumizu
2016	—	`conf`	Differential Privacy without Sensitivity. NIPS Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa