{"id":"https://openalex.org/W4376852246","doi":"https://doi.org/10.1145/3564121.3564139","title":"Accurate and Efficient Channel pruning via Orthogonal Matching Pursuit","display_name":"Accurate and Efficient Channel pruning via Orthogonal Matching Pursuit","publication_year":2022,"publication_date":"2022-10-12","ids":{"openalex":"https://openalex.org/W4376852246","doi":"https://doi.org/10.1145/3564121.3564139"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3564121.3564139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5009272947","display_name":"Kiran Purohit","orcid":"https://orcid.org/0000-0002-5512-3441"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"funder","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kiran Purohit","raw_affiliation_strings":["Department of Computer Science and Engineering, IIT Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091958537","display_name":"Anurag Reddy Parvathgari","orcid":"https://orcid.org/0000-0001-5501-4862"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"funder","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anurag Parvathgari","raw_affiliation_strings":["Department of Computer Science and Engineering, IIT Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103201369","display_name":"Soumi Das","orcid":"https://orcid.org/0000-0002-6933-5744"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"funder","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Soumi Das","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046910575","display_name":"Sourangshu Bhattacharya","orcid":"https://orcid.org/0000-0001-5220-1881"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"funder","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sourangshu Bhattacharya","raw_affiliation_strings":["Department of Computer Science and Technology, IIT KHARAGPUR, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, IIT KHARAGPUR, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":59},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9867,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9851,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.80649936},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.72061926}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.93680817},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.80649936},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.72061926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7167485},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.676508},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6375078},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5088311},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4873572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45239252},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.18871337},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1523917},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3564121.3564139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.46,"id":"https://metadata.un.org/sdg/9"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":16,"referenced_works":["https://openalex.org/W2127271355","https://openalex.org/W2137842291","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2736536388","https://openalex.org/W2928560789","https://openalex.org/W2962851801","https://openalex.org/W2963145730","https://openalex.org/W2963363373","https://openalex.org/W2963446712","https://openalex.org/W2964233199","https://openalex.org/W2984618279","https://openalex.org/W3034513523","https://openalex.org/W3035467254","https://openalex.org/W3174700868","https://openalex.org/W3204367575"],"related_works":["https://openalex.org/W4220674950","https://openalex.org/W3130682819","https://openalex.org/W2806946907","https://openalex.org/W2785927776","https://openalex.org/W2381915087","https://openalex.org/W2103001330","https://openalex.org/W2073241848","https://openalex.org/W2042644197","https://openalex.org/W2020549994","https://openalex.org/W1980565639"],"abstract_inverted_index":{"The":[0],"deeper":[1],"and":[2,29,46,66,142,171],"wider":[3],"architectures":[4],"of":[5,38,61,81,107,109,112,118,135,179,196],"recent":[6],"convolutional":[7],"neural":[8],"networks":[9],"(CNN)":[10],"are":[11],"responsible":[12],"for":[13,44,54,75,93],"superior":[14],"performance":[15],"in":[16],"computer":[17],"vision":[18],"tasks.":[19],"However,":[20],"they":[21],"also":[22,99],"come":[23],"with":[24,130],"an":[25,86],"enormous":[26],"model":[27],"size":[28,134],"heavy":[30],"computational":[31],"cost.":[32],"Filter":[33],"pruning":[34,95],"(FP)":[35],"is":[36],"one":[37],"the":[39,59,62,105,116,128,160,193],"methods":[40],"applied":[41],"to":[42],"CNNs":[43],"compression":[45],"acceleration.":[47],"Various":[48],"techniques":[49],"have":[50],"been":[51],"recently":[52],"proposed":[53],"filter":[55,76,82,94,136],"pruning.":[56],"We":[57,70,84,98,138,167],"address":[58,104],"limitation":[60],"existing":[63],"state-of-the-art":[64],"method":[65,74,162],"motivate":[67],"our":[68],"setup.":[69],"develop":[71],"a":[72,119,124,131],"novel":[73],"selection":[77],"using":[78,148],"sparse":[79],"approximation":[80],"weights.":[83],"propose":[85,100],"orthogonal":[87],"matching":[88],"pursuit":[89],"(OMP)":[90],"based":[91],"algorithm":[92],"(called":[96],"FP-OMP).":[97],"FP-OMP":[101,121,141,143,156,174,190],"Search,":[102],"which":[103],"problem":[106],"removal":[108],"uniform":[110],"number":[111,178],"filters":[113,180],"from":[114,181],"all":[115,127],"layers":[117,129],"network.":[120],"Search":[122,144,157,175],"performs":[123],"search":[125],"over":[126,192],"given":[132],"batch":[133],"removal.":[137],"evaluate":[139],"both":[140,169],"on":[145],"benchmark":[146],"datasets":[147],"standard":[149],"ResNet":[150],"architectures.":[151],"Experimental":[152],"results":[153],"indicate":[154],"that":[155,173,189],"consistently":[158],"outperforms":[159],"baseline":[161],"(LRF)":[163],"by":[164],"nearly":[165],".":[166],"demonstrate":[168],"empirically":[170],"visually,":[172],"prunes":[176],"different":[177,182],"layers.":[183],"Further,":[184],"timing":[185],"profile":[186],"experiments":[187],"show":[188],"improves":[191],"running":[194],"time":[195],"LRF.":[197]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4376852246","counts_by_year":[],"updated_date":"2025-02-27T09:28:44.758675","created_date":"2023-05-18"}