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20172020
most citedRecent Developments in Boolean Matrix Factorization

6 citations · 9 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG20201 cited

Biclustering and Boolean Matrix Factorization in Data Streams

Stefan Neumann, Pauli Miettinen

We study the clustering of bipartite graphs and Boolean matrix factorization in data streams. We consider a streaming setting in which the vertices from the left side of the graph…

cs.LG20206 cited

Recent Developments in Boolean Matrix Factorization

Pauli Miettinen, Stefan Neumann

The goal of Boolean Matrix Factorization (BMF) is to approximate a given binary matrix as the product of two low-rank binary factor matrices, where the product of the factor matric…

cs.DS20192 cited

Boolean matrix factorization meets consecutive ones property

Nikolaj Tatti, Pauli Miettinen

Boolean matrix factorization is a natural and a popular technique for summarizing binary matrices. In this paper, we study a problem of Boolean matrix factorization where we additi…

cs.AI2018

Hybrid ASP-based Approach to Pattern Mining

Sergey Paramonov, Daria Stepanova, Pauli Miettinen

Detecting small sets of relevant patterns from a given dataset is a central challenge in data mining. The relevance of a pattern is based on user-provided criteria; typically, all…

cs.LG2018

Latitude: A Model for Mixed Linear-Tropical Matrix Factorization

Sanjar Karaev, James Hook, Pauli Miettinen

Nonnegative matrix factorization (NMF) is one of the most frequently-used matrix factorization models in data analysis. A significant reason to the popularity of NMF is its interpr…

cs.CC2017

Reductions for Frequency-Based Data Mining Problems

Stefan Neumann, Pauli Miettinen

Studying the computational complexity of problems is one of the - if not the - fundamental questions in computer science. Yet, surprisingly little is known about the computational…