Kentaro Minami

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 18

Top Topics

Kullback Leibler

Efficient Learning

Variational Inference

Stock Price Prediction

Top Venues

Publications

Masanori Hirano, Kentaro Minami, Kentaro Imajo
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. CoRR (2023)
Masanori Hirano, Kentaro Imajo, Kentaro Minami, Takuya Shimada
Efficient Learning of Nested Deep Hedging using Multiple Options. IIAI-AAI (2023)
Masanori Hirano, Kentaro Minami, Kentaro Imajo
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. ICAIF (2023)
Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano
Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study. CoRR (2023)
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)
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 (2022)
Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. Big Data (2022)
Ziyin Liu, Kentaro Minami, Kentaro Imajo
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction. ICAIF (2022)
Yugo Fujimotol, Kei Nakagawa, Kentaro Imajo, Kentaro Minami
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty. CoRR (2022)
Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal
Contrastive Representation Learning with Trainable Augmentation Channel. CoRR (2021)
Kentaro Imajo, Kentaro Minami, Katsuya Ito, Kei Nakagawa
Deep Portfolio Optimization via Distributional Prediction of Residual Factors. AAAI (2021)
Ziyin Liu, Kentaro Minami, Kentaro Imajo
What Data Augmentation Do We Need for Deep-Learning-Based Finance? CoRR (2021)
Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa
Trader-Company Method: A Metaheuristics for Interpretable Stock Price Prediction. AAMAS (2021)
Kentaro Minami
Degrees of freedom in submodular regularization: A computational perspective of Stein's unbiased risk estimate. J. Multivar. Anal. 175 (2020)
Casey Chu, Kentaro Minami, Kenji Fukumizu
Smoothness and Stability in GANs. CoRR (2020)
Casey Chu, Kentaro Minami, Kenji Fukumizu
Smoothness and Stability in GANs. ICLR (2020)
Casey Chu, Kentaro Minami, Kenji Fukumizu
The equivalence between Stein variational gradient descent and black-box variational inference. CoRR (2020)
Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa
Differential Privacy without Sensitivity. NIPS (2016)