22 citations · 37 across the 9 of their papers we have counts for
21 papers
Temporal Portability of Numeric User Metadata on Twitter
Chako Takahashi, Mitsuo Yoshida, Muneki Yasuda
Numeric user metadata in social media are often reused over time. However, their reusability may depend on what an analysis needs to preserve. We introduce temporal portability as…
Effective Method for Inverse Ising Problem under Missing Observations in Restricted Boltzmann Machines
Kaiji Sekimoto, Muneki Yasuda
Restricted Boltzmann machines (RBMs) are energy-based models analogous to the Ising model and are widely applied in statistical machine learning. The standard inverse Ising problem…
Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine
Kaiji Sekimoto, Muneki Yasuda
Gaussian-Bernoulli restricted Boltzmann machines (GBRBMs) are often used for semi-supervised anomaly detection, where they are trained using only normal data points. In GBRBM-based…
Multi-layered Discriminative Restricted Boltzmann Machine with Untrained Probabilistic Layer
Yuri Kanno, Muneki Yasuda
An extreme learning machine (ELM) is a three-layered feed-forward neural network having untrained parameters, which are randomly determined before training. Inspired by the idea of…
Free Energy Evaluation Using Marginalized Annealed Importance Sampling
Muneki Yasuda, Chako Takahashi
The evaluation of the free energy of a stochastic model is considered a significant issue in various fields of physics and machine learning. However, the exact free energy evaluati…
Composite Spatial Monte Carlo Integration Based on Generalized Least Squares
Kaiji Sekimoto, Muneki Yasuda
Although evaluation of the expectations on the Ising model is essential in various applications, it is mostly infeasible because of intractable multiple summations. Spatial Monte C…