67 citations · 105 across the 7 of their papers we have counts for
8 papers
Accelerating jackknife resampling for the Canonical Polyadic Decomposition
Christos Psarras, Lars Karlsson, Rasmus Bro +1
The Canonical Polyadic (CP) tensor decomposition is frequently used as a model in applications in a variety of different fields. Using jackknife resampling to estimate parameter un…
An AO-ADMM approach to constraining PARAFAC2 on all modes
Marie Roald, Carla Schenker, Vince D. Calhoun +4
Analyzing multi-way measurements with variations across one mode of the dataset is a challenge in various fields including data mining, neuroscience and chemometrics. For example,…
Concurrent Alternating Least Squares for multiple simultaneous Canonical Polyadic Decompositions
Christos Psarras, Lars Karlsson, Rasmus Bro +1
Tensor decompositions, such as CANDECOMP/PARAFAC (CP), are widely used in a variety of applications, such as chemometrics, signal processing, and machine learning. A broadly used m…
Interpretable Feature Learning in Multivariate Big Data Analysis for Network Monitoring
José Camacho, Katarzyna Wasielewska, Rasmus Bro +1
There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitor…
Cross-product Penalized Component Analysis (XCAN)
José Camacho, Evrim Acar, Morten A. Rasmussen +1
Matrix factorization methods are extensively employed to understand complex data. In this paper, we introduce the cross-product penalized component analysis (XCAN), a sparse matrix…
Nonnegative PARAFAC2: a flexible coupling approach
Jeremy E. Cohen, Rasmus Bro
Modeling variability in tensor decomposition methods is one of the challenges of source separation. One possible solution to account for variations from one data set to another, jo…