{"id":{"repo_id":"umn","oai_identifier":"oai:conservancy.umn.edu:11299/173949"},"canonical_url":"https://search.dev.ndltd.org/etd/umn/oai:conservancy.umn.edu:11299/173949","repository":{"repo_id":"umn","name":"University of Minnesota","base_url":"https://conservancy.umn.edu/server/oai/request"},"display":{"title":"Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization","abstract":"Problems with non-negativity constrains have recently attracted a great deal of interest. Non-negativity constraints arise naturally in many applications, and are often necessary for proper interpretation. Furthermore, these constrains provide an intrinsic sparsity that may be of value in certain situations. Two common problems that have gathered notable attention are the non-negative least squares (NNLS) problem, and the nonnegative matrix factorization (NMF) problem. In this paper, a method to solve the NNLS problem in an adaptive way is discussed. Additionally, possible ways to apply this, and other related method, to adaptive NMF problems are discussed.","abstract_html":"Problems with non-negativity constrains have recently attracted a great deal of interest. Non-negativity constraints arise naturally in many applications, and are often necessary for proper interpretation. Furthermore, these constrains provide an intrinsic sparsity that may be of value in certain situations. Two common problems that have gathered notable attention are the non-negative least squares (NNLS) problem, and the nonnegative matrix factorization (NMF) problem. In this paper, a method to solve the NNLS problem in an adaptive way is discussed. Additionally, possible ways to apply this, and other related method, to adaptive NMF problems are discussed.","abstract_has_math":false,"creators":["Mosesov, Artem"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-06","date_published":"2014-06","updated_at":"2026-07-24T05:19:52Z","subjects":["least squares","matrix factorization","NMF","NNLS","Nonnegative"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11299/173949","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Mosesov, Artem"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-08-19T18:37:09Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-08-19T18:37:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2014-06"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["least squares","matrix factorization","NMF","NNLS","Nonnegative"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11299/173949"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["University of Minnesota M.S.E.E. thesis. June 2014. Major: Electrical Engineering. Advisor: Nikolaos Sidiropoulos. 1 computer file (PDF); v, 38 pages."]},{"key":"dc:description.abstract","label":"Abstract","values":["Problems with non-negativity constrains have recently attracted a great deal of interest. Non-negativity constraints arise naturally in many applications, and are often necessary for proper interpretation. Furthermore, these constrains provide an intrinsic sparsity that may be of value in certain situations. Two common problems that have gathered notable attention are the non-negative least squares (NNLS) problem, and the nonnegative matrix factorization (NMF) problem. In this paper, a method to solve the NNLS problem in an adaptive way is discussed. Additionally, possible ways to apply this, and other related method, to adaptive NMF problems are discussed."]},{"key":"dc:title","label":"Title","values":["Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization"]}]}],"canonical_facts":{"dc:creator":["Mosesov, Artem"],"dc:date.accessioned":["2015-08-19T18:37:09Z"],"dc:date.available":["2015-08-19T18:37:09Z"],"dc:date.issued":["2014-06"],"dc:description":["University of Minnesota M.S.E.E. thesis. June 2014. Major: Electrical Engineering. Advisor: Nikolaos Sidiropoulos. 1 computer file (PDF); v, 38 pages."],"dc:description.abstract":["Problems with non-negativity constrains have recently attracted a great deal of interest. Non-negativity constraints arise naturally in many applications, and are often necessary for proper interpretation. Furthermore, these constrains provide an intrinsic sparsity that may be of value in certain situations. Two common problems that have gathered notable attention are the non-negative least squares (NNLS) problem, and the nonnegative matrix factorization (NMF) problem. In this paper, a method to solve the NNLS problem in an adaptive way is discussed. Additionally, possible ways to apply this, and other related method, to adaptive NMF problems are discussed."],"dc:identifier.uri":["http://hdl.handle.net/11299/173949"],"dc:language.iso":["en"],"dc:subject":["least squares","matrix factorization","NMF","NNLS","Nonnegative"],"dc:title":["Adaptive Non-negative Least Squares with Applications to Non-Negative Matrix Factorization"],"dc:type":["Thesis or Dissertation"]},"updated_at":"2026-07-24T05:19:52Z"}