39 citations · 102 across the 6 of their papers we have counts for
6 papers · 1 filter
Loss function based second-order Jensen inequality and its application to particle variational inference
Futoshi Futami, Tomoharu Iwata, Naonori Ueda +2
Bayesian model averaging, obtained as the expectation of a likelihood function by a posterior distribution, has been widely used for prediction, evaluation of uncertainty, and mode…
Anomaly Detection with Inexact Labels
Tomoharu Iwata, Machiko Toyoda, Shotaro Tora +1
We propose a supervised anomaly detection method for data with inexact anomaly labels, where each label, which is assigned to a set of instances, indicates that at least one instan…
Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information
Maya Okawa, Tomoharu Iwata, Takeshi Kurashima +3
Predicting when and where events will occur in cities, like taxi pick-ups, crimes, and vehicle collisions, is a challenging and important problem with many applications in fields s…
Unsupervised Object Matching for Relational Data
Tomoharu Iwata, Naonori Ueda
We propose an unsupervised object matching method for relational data, which finds matchings between objects in different relational datasets without correspondence information. Fo…
Partial AUC Maximization via Nonlinear Scoring Functions
Naonori Ueda, Akinori Fujino
We propose a method for maximizing a partial area under a receiver operating characteristic (ROC) curve (pAUC) for binary classification tasks. In binary classification tasks, accu…
Multi-output Polynomial Networks and Factorization Machines
Mathieu Blondel, Vlad Niculae, Takuma Otsuka +1
Factorization machines and polynomial networks are supervised polynomial models based on an efficient low-rank decomposition. We extend these models to the multi-output setting, i.…