{"id":"https://openalex.org/W2884913559","doi":"https://doi.org/10.1080/08839514.2018.1486131","title":"Sparse Connectivity and Activity Using Sequential Feature Selection in Supervised Learning","display_name":"Sparse Connectivity and Activity Using Sequential Feature Selection in Supervised Learning","publication_year":2018,"publication_date":"2018-07-03","ids":{"openalex":"https://openalex.org/W2884913559","doi":"https://doi.org/10.1080/08839514.2018.1486131","mag":"2884913559"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2018.1486131","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2018.1486131","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5089855050","display_name":"Fariba Nasiriyan","orcid":null},"institutions":[{"id":"https://openalex.org/I167694869","display_name":"Bu-Ali Sina University","ror":"https://ror.org/04ka8rx28","country_code":"IR","type":"education","lineage":["https://openalex.org/I167694869"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Fariba Nasiriyan","raw_affiliation_strings":["Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran","institution_ids":["https://openalex.org/I167694869"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050131337","display_name":"Hassan Khotanlou","orcid":"https://orcid.org/0000-0001-7351-9397"},"institutions":[{"id":"https://openalex.org/I167694869","display_name":"Bu-Ali Sina University","ror":"https://ror.org/04ka8rx28","country_code":"IR","type":"education","lineage":["https://openalex.org/I167694869"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Hassan Khotanlou","raw_affiliation_strings":["Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran","institution_ids":["https://openalex.org/I167694869"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050131337"],"corresponding_institution_ids":["https://openalex.org/I167694869"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":0.2081,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5101797,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"32","issue":"6","first_page":"568","last_page":"581"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9987000226974487,"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/mnist-database","display_name":"MNIST database","score":0.9275574684143066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8680812120437622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7050041556358337},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6187576651573181},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5441908836364746},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5334295034408569},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5198050737380981},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4791514277458191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.479099303483963},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47739285230636597},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4570671319961548},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44841235876083374},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4475760757923126},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.4254564940929413},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4244294762611389},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4118930995464325},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16329622268676758},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09466901421546936}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.9275574684143066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8680812120437622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7050041556358337},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6187576651573181},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5441908836364746},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5334295034408569},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5198050737380981},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4791514277458191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.479099303483963},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47739285230636597},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4570671319961548},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44841235876083374},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4475760757923126},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.4254564940929413},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4244294762611389},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4118930995464325},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16329622268676758},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09466901421546936},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2018.1486131","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2018.1486131","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9d1ff90f683e4218b7f710ba6393162a","is_oa":false,"landing_page_url":"https://doaj.org/article/9d1ff90f683e4218b7f710ba6393162a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 32, Iss 6, Pp 568-581 (2018)","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W7299809","https://openalex.org/W1497354029","https://openalex.org/W1497941563","https://openalex.org/W1514337951","https://openalex.org/W1521633888","https://openalex.org/W1554663460","https://openalex.org/W1582211066","https://openalex.org/W1606544556","https://openalex.org/W1673167037","https://openalex.org/W1673584506","https://openalex.org/W1976738367","https://openalex.org/W2028781966","https://openalex.org/W2050834445","https://openalex.org/W2058670155","https://openalex.org/W2074376560","https://openalex.org/W2080968155","https://openalex.org/W2105464873","https://openalex.org/W2110198170","https://openalex.org/W2111854888","https://openalex.org/W2115205382","https://openalex.org/W2116360511","https://openalex.org/W2118103795","https://openalex.org/W2118718620","https://openalex.org/W2132424367","https://openalex.org/W2137677098","https://openalex.org/W2152617511","https://openalex.org/W2156163116","https://openalex.org/W2189183509","https://openalex.org/W2798766386","https://openalex.org/W4238135117","https://openalex.org/W4242209908","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2590796488","https://openalex.org/W4389249638","https://openalex.org/W2734358244","https://openalex.org/W2750384547","https://openalex.org/W2809732489"],"abstract_inverted_index":{"Generally,":[0],"in":[1,10,103],"neural":[2,106,131],"networks":[3],"the":[4,29,54,74,84,90,104,109,126,129,152],"sparseness":[5,61,91],"is":[6,36,50,77,87],"a":[7,11,59,100],"suitable":[8],"regularizer":[9],"lot":[12],"of":[13,31,128,142],"applications.":[14],"In":[15],"this":[16,161],"paper,":[17],"sparse":[18,21],"connectivity":[19],"and":[20,43,108,150,154],"representation":[22],"are":[23],"used":[24,51,123,147],"to":[25,28,39,52,124,133,148],"enhance":[26],"solutions":[27],"problem":[30],"classification.":[32],"Sequential":[33],"feature":[34],"selection":[35],"then":[37],"leveraged":[38],"remove":[40],"redundant":[41],"features":[42],"select":[44],"relevant":[45],"ones.":[46],"Sparseness-enforcing":[47],"projection":[48,93],"operator":[49,76],"discovering":[53],"most":[55],"similar":[56],"vector":[57,66],"with":[58],"predefined":[60],"degree":[62],"for":[63,97],"any":[64],"input":[65],"as":[67,99],"well.":[68],"As":[69],"it":[70,86],"will":[71],"be":[72,95,112],"argued,":[73],"mentioned":[75],"approximately":[78],"differentiable":[79],"at":[80],"every":[81],"point.":[82],"From":[83],"facts":[85],"clear":[88],"that":[89],"enforcing":[92],"would":[94],"appropriate":[96],"use":[98],"transfer":[101],"function":[102],"proposed":[105,130],"network":[107,110,132],"can":[111],"tuned":[113],"using":[114],"gradient":[115],"based":[116],"methods.":[117],"Meanwhile,":[118],"an":[119],"intelligent":[120],"method":[121,153],"was":[122,146,157],"build":[125],"architecture":[127],"achieve":[134],"better":[135],"performance.":[136],"The":[137],"MNIST":[138],"dataset":[139],"which":[140],"consists":[141],"70,000":[143],"handwritten":[144],"digits":[145],"train":[149],"test":[151],"99.18%":[155],"accuracy":[156],"achieved":[158],"by":[159],"classifying":[160],"dataset.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}