Group Sparsity in Nonnegative Matrix Factorization

  title={Group Sparsity in Nonnegative Matrix Factorization},
  author={Jingu Kim and Renato D. C. Monteiro and Haesun Park},
A recent challenge in data analysis for science and engineering is that data are often represented in a structured way. In particular, many data mining tasks have to deal with group-structured prior information, where features or data items are organized into groups. In this paper, we develop group sparsity regularization methods for nonnegative matrix factorization (NMF). NMF is an effective data mining tool that has been widely adopted in text mining, bioinformatics, and clustering, but a… CONTINUE READING
Highly Cited
This paper has 58 citations. REVIEW CITATIONS
37 Citations
35 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 37 extracted citations

58 Citations

Citations per Year
Semantic Scholar estimates that this publication has 58 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…