Kohei Miyaguchi

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 23

Top Topics

Optimization Methods

Minimum Description Length

Top Venues

Publications

Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima
Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables. CoRR (2024)
Hirota Kinoshita, Takayuki Osogami, Kohei Miyaguchi
Socially efficient mechanism on the minimum budget. CoRR (2024)
Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami
Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies. ICML (2023)
Kohei Miyaguchi
A Theoretical Framework of Almost Hyperparameter-free Hyperparameter Selection Methods for Offline Policy Evaluation. CoRR (2022)
Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima
Detection of Unobserved Common Cause in Discrete Data Based on the MDL Principle. Big Data (2022)
Hiroki Yanagisawa, Kohei Miyaguchi, Takayuki Katsuki
Hierarchical Lattice Layer for Partially Monotone Neural Networks. NeurIPS (2022)
Takayuki Katsuki, Kohei Miyaguchi, Akira Koseki, Toshiya Iwamori, Ryosuke Yanagiya, Atsushi Suzuki
Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction. CoRR (2022)
Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami
Biases in In Silico Evaluation of Molecular Optimization Methods and Bias-Reduced Evaluation Methodology. CoRR (2022)
Takayuki Katsuki, Kohei Miyaguchi, Akira Koseki, Toshiya Iwamori, Ryosuke Yanagiya, Atsushi Suzuki
Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction. IJCAI (2022)
Kohei Miyaguchi, Takayuki Katsuki, Akira Koseki, Toshiya Iwamori
Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion. ICLR (2022)
Kohei Miyaguchi
Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models. NeurIPS (2021)
Kohei Miyaguchi
PAC-Bayesian Transportation Bound. CoRR (2019)
Kohei Miyaguchi, Hiroshi Kajino
Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting. AAAI (2019)
Kohei Miyaguchi, Kenji Yamanishi
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity. AISTATS (2019)
Kohei Miyaguchi, Kenji Yamanishi
High-dimensional Penalty Selection via Minimum Description Length Principle. CoRR (2018)
Kohei Miyaguchi, Kenji Yamanishi
-Balls via Envelope Complexity. CoRR (2018)
Kohei Miyaguchi, Kenji Yamanishi
High-dimensional penalty selection via minimum description length principle. Mach. Learn. 107 (8-10) (2018)
Kohei Miyaguchi, Shin Matsushima, Kenji Yamanishi
Sparse Graphical Modeling via Stochastic Complexity. SDM (2017)
Kohei Miyaguchi, Kenji Yamanishi
Online detection of continuous changes in stochastic processes. Int. J. Data Sci. Anal. 3 (3) (2017)
Kohei Miyaguchi
Normalized Maximum Likelihood with Luckiness for Multivariate Normal Distributions. CoRR (2017)
Ryoya Kaneko, Kohei Miyaguchi, Kenji Yamanishi
Detecting changes in streaming data with information-theoretic windowing. IEEE BigData (2017)
Kenji Yamanishi, Kohei Miyaguchi
Detecting gradual changes from data stream using MDL-change statistics. IEEE BigData (2016)
Atsushi Suzuki, Kohei Miyaguchi, Kenji Yamanishi
Structure Selection for Convolutive Non-negative Matrix Factorization Using Normalized Maximum Likelihood Coding. ICDM (2016)
Kohei Miyaguchi, Kenji Yamanishi
On-line detection of continuous changes in stochastic processes. DSAA (2015)