{"id":"https://openalex.org/W4404037418","doi":"https://doi.org/10.1109/mlsp58920.2024.10734736","title":"Self Supervised Dictionary Learning Using Kernel Matching","display_name":"Self Supervised Dictionary Learning Using Kernel Matching","publication_year":2024,"publication_date":"2024-09-22","ids":{"openalex":"https://openalex.org/W4404037418","doi":"https://doi.org/10.1109/mlsp58920.2024.10734736"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp58920.2024.10734736","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp58920.2024.10734736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114549621","display_name":"Shubham Choudhary","orcid":"https://orcid.org/0009-0006-3838-0389"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shubham Choudhary","raw_affiliation_strings":["School of Engineering and Applied Science, Harvard University"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Science, Harvard University","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087212561","display_name":"Paul Masset","orcid":"https://orcid.org/0000-0003-2001-7515"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Paul Masset","raw_affiliation_strings":["McGill University,Department of Psychology"],"affiliations":[{"raw_affiliation_string":"McGill University,Department of Psychology","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002643771","display_name":"Demba Ba","orcid":"https://orcid.org/0000-0002-1139-1030"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Demba Ba","raw_affiliation_strings":["School of Engineering and Applied Science, Harvard University"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Science, Harvard University","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114549621"],"corresponding_institution_ids":["https://openalex.org/I136199984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17040145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.8737999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.8737999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.8555999994277954,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7654425501823425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6712386608123779},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5339466333389282},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.5076028108596802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48778730630874634},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45209652185440063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42565885186195374},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.41561904549598694},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11396566033363342},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.09620136022567749},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0608198344707489}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7654425501823425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6712386608123779},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5339466333389282},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.5076028108596802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48778730630874634},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45209652185440063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42565885186195374},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.41561904549598694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11396566033363342},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.09620136022567749},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0608198344707489},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp58920.2024.10734736","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp58920.2024.10734736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2101234009","https://openalex.org/W2145889472","https://openalex.org/W2157364932","https://openalex.org/W2735683573","https://openalex.org/W2842511635","https://openalex.org/W4292363360","https://openalex.org/W4297808394","https://openalex.org/W4387587755","https://openalex.org/W6691766336","https://openalex.org/W6774314701","https://openalex.org/W6810007534"],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W4301594054","https://openalex.org/W2794488505","https://openalex.org/W2961085424","https://openalex.org/W2513638114","https://openalex.org/W4390062853","https://openalex.org/W2340127552","https://openalex.org/W4389256085","https://openalex.org/W3210156800","https://openalex.org/W3033485676"],"abstract_inverted_index":{"We":[0,15,52],"introduce":[1],"a":[2,20,55,82,96],"self":[3],"supervised":[4],"framework":[5,45],"for":[6,99],"learning":[7,50,86,113,118],"representations":[8,87,105],"in":[9,111,116],"the":[10,17,25,28,34,44,67,72,100,103],"context":[11],"of":[12,60,85],"dictionary":[13],"learning.":[14],"cast":[16],"problem":[18,69],"as":[19],"kernel":[21,89],"matching":[22],"task":[23],"between":[24],"input":[26],"and":[27,70,119],"representation":[29,112],"space,":[30],"with":[31,88],"constraints":[32],"on":[33],"latent":[35],"kernel.":[36],"By":[37],"adjusting":[38],"these":[39],"constraints,":[40,90],"we":[41],"demonstrate":[42],"how":[43],"can":[46,107],"adapt":[47],"to":[48,65,74],"different":[49],"objectives.":[51],"then":[53],"formulate":[54],"novel":[56],"Alternate":[57],"Direction":[58],"Method":[59],"Multipli-ers":[61],"(ADMM)":[62],"based":[63],"algorithm":[64],"solve":[66],"optimization":[68],"connect":[71],"dynamics":[73],"classical":[75],"alternate":[76],"minimization":[77],"techniques.":[78],"This":[79],"approach":[80],"offers":[81],"unique":[83],"way":[84],"that":[91],"enable":[92],"us":[93],"implicitly":[94],"learn":[95],"generative":[97],"map":[98],"data":[101],"from":[102],"learned":[104],"which":[106],"have":[108],"broad":[109],"applications":[110],"tasks":[114],"both":[115],"machine":[117],"neuro-science.":[120]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}