77 citations · 371 across the 21 of their papers we have counts for
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Machine-learning Selection of Optical Transients in Subaru/Hyper Suprime-Cam Survey
Mikio Morii, Shiro Ikeda, Nozomu Tominaga +8
We present an application of machine-learning (ML) techniques to source selection in the optical transient survey data with Hyper Suprime-Cam (HSC) on the Subaru telescope. Our goa…
Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms
Mathieu Blondel, Masakazu Ishihata, Akinori Fujino +1
Polynomial networks and factorization machines are two recently-proposed models that can efficiently use feature interactions in classification and regression tasks. In this paper,…
Higher-Order Factorization Machines
Mathieu Blondel, Akinori Fujino, Naonori Ueda +1
Factorization machines (FMs) are a supervised learning approach that can use second-order feature combinations even when the data is very high-dimensional. Unfortunately, despite i…