51 citations · 96 across the 7 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2016★ 38 cited
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,…
stat.ML2016★ 51 cited
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…