7 citations · 7 across the 3 of their papers we have counts for
4 papers
Distributed Bayesian Piecewise Sparse Linear Models
Masato Asahara, Ryohei Fujimaki
The importance of interpretability of machine learning models has been increasing due to emerging enterprise predictive analytics, threat of data privacy, accountability of artific…
Optimization Beyond Prediction: Prescriptive Price Optimization
Shinji Ito, Ryohei Fujimaki
This paper addresses a novel data science problem, prescriptive price optimization, which derives the optimal price strategy to maximize future profit/revenue on the basis of massi…
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models
Shaohua Li, Ryohei Fujimaki, Chunyan Miao
Factorial hidden Markov models (FHMMs) are powerful tools of modeling sequential data. Learning FHMMs yields a challenging simultaneous model selection issue, i.e., selecting the n…
Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood
Kohei Hayashi, Shin-ichi Maeda, Ryohei Fujimaki
Factorized information criterion (FIC) is a recently developed approximation technique for the marginal log-likelihood, which provides an automatic model selection framework for a…