{"id":"https://openalex.org/W2035803309","doi":"https://doi.org/10.1109/bigdata.2014.7004351","title":"Fast learning for big data applications using parameterized multilayer perceptron","display_name":"Fast learning for big data applications using parameterized multilayer perceptron","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2035803309","doi":"https://doi.org/10.1109/bigdata.2014.7004351","mag":"2035803309"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","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/A5043943508","display_name":"B. Chandra","orcid":"https://orcid.org/0000-0002-7017-5944"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. Chandra","raw_affiliation_strings":["Indraprastha Institute of Information Technology Delhi, New Delhi, Delhi, IN","Department of Mathematics, IIT New Delhi 110016"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indraprastha Institute of Information Technology Delhi, New Delhi, Delhi, IN","institution_ids":["https://openalex.org/I119939252"]},{"raw_affiliation_string":"Department of Mathematics, IIT New Delhi 110016","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101921248","display_name":"Rajesh Kumar Sharma","orcid":"https://orcid.org/0000-0002-2675-4623"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajesh Kumar Sharma","raw_affiliation_strings":["Indraprastha Institute of Information Technology Delhi, New Delhi, Delhi, IN","Department of Mathematics, IIT New Delhi 110016"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indraprastha Institute of Information Technology Delhi, New Delhi, Delhi, IN","institution_ids":["https://openalex.org/I119939252"]},{"raw_affiliation_string":"Department of Mathematics, IIT New Delhi 110016","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8458,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81166668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"11","issue":null,"first_page":"17","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.9049780368804932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7072870135307312},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.652825653553009},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6090553402900696},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5990346670150757},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4835960268974304},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4658993184566498},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4423052668571472},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4021153450012207},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35706228017807007},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32991015911102295},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30213987827301025}],"concepts":[{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.9049780368804932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7072870135307312},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.652825653553009},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6090553402900696},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5990346670150757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4835960268974304},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4658993184566498},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4423052668571472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4021153450012207},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35706228017807007},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32991015911102295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30213987827301025},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2014.7004351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.550000011920929}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320721","display_name":"Council of Scientific and Industrial Research, India","ror":"https://ror.org/021wm7p51"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1498436455","https://openalex.org/W1968464152","https://openalex.org/W2060929823","https://openalex.org/W2062227835","https://openalex.org/W2081700482","https://openalex.org/W2117499988","https://openalex.org/W2125906362","https://openalex.org/W2136922672","https://openalex.org/W2137841648","https://openalex.org/W2145094598","https://openalex.org/W2218318129","https://openalex.org/W2359973477","https://openalex.org/W2997574889","https://openalex.org/W6629815555","https://openalex.org/W6677604277","https://openalex.org/W6678534324","https://openalex.org/W6681096077","https://openalex.org/W6688386640"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2136232598"],"abstract_inverted_index":{"An":[0],"innovative":[1],"approach":[2],"has":[3,39,46],"been":[4,40,47],"proposed":[5,41],"for":[6,9,24,67,105],"using":[7,22,49],"MLP":[8,23,93],"handling":[10,106],"Big":[11,27,107],"data.":[12,108],"There":[13],"is":[14,72,101],"high":[15],"computational":[16,88],"cost":[17],"and":[18],"time":[19,89],"involved":[20],"in":[21,80,87],"classification":[25,81],"of":[26,32],"data":[28],"having":[29],"large":[30,97],"number":[31],"features.":[33],"A":[34],"parameterized":[35,48],"multilayer":[36],"perceptron":[37],"(PMLP)":[38],"where":[42],"the":[43,55,69],"weight":[44,56,70],"matrix":[45,71],"periodic":[50],"functions.":[51],"This":[52,75,100],"ensures":[53],"that":[54],"values":[57],"are":[58],"bounded":[59],"which":[60],"leads":[61,77],"to":[62,78,92],"inherent":[63],"regularization.":[64],"Memory":[65],"requirements":[66],"storing":[68],"drastically":[73],"reduced.":[74],"also":[76],"increase":[79],"accuracy":[82],"associated":[83],"with":[84],"drastic":[85],"reduction":[86],"as":[90],"compared":[91],"when":[94],"executed":[95],"on":[96],"benchmark":[98],"datasets.":[99],"a":[102],"promising":[103],"technique":[104]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
