Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions...
This paper addresses the problem of segmenting lowlevel
partial feature point tracks belonging to multiple motions.
We show that the local velocity vectors at each instant
of th...
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
As nonnegative tensor factorization (NTF) is particularly useful for the problem of underdetermined linear transform model, we performed NTF on the EEG data recorded from 14 electr...
Fengyu Cong, Anh Huy Phan, Piia Astikainen, Qibin ...