{"id":"https://openalex.org/W2899025077","doi":"https://doi.org/10.1109/mlsp.2018.8516987","title":"SIMPLE DEEP LEARNING NETWORK VIA TENSOR-TRAIN HAAR-WAVELET DECOMPOSITION WITHOUT RETRAINING","display_name":"SIMPLE DEEP LEARNING NETWORK VIA TENSOR-TRAIN HAAR-WAVELET DECOMPOSITION WITHOUT RETRAINING","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2899025077","doi":"https://doi.org/10.1109/mlsp.2018.8516987","mag":"2899025077"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2018.8516987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2018.8516987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 28th 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/A5038169312","display_name":"Weizhi Huang","orcid":"https://orcid.org/0000-0002-1090-8528"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wei-Zhi Huang","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Taipei, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taipei, Taiwan, ROC","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018491742","display_name":"Sung-Hsien Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sung-Hsien Hsieh","raw_affiliation_strings":["Graduate Inst. Comm. Eng., National Taiwan University, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Inst. Comm. Eng., National Taiwan University, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042784674","display_name":"Chun-Shien Lu","orcid":"https://orcid.org/0000-0002-5900-0019"},"institutions":[{"id":"https://openalex.org/I4210086894","display_name":"Research Center for Information Technology Innovation, Academia Sinica","ror":"https://ror.org/000zgvm20","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210086894","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun-Shien Lu","raw_affiliation_strings":["Research Center for Information Technology Innovation, Academia Sinica, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Information Technology Innovation, Academia Sinica, Taiwan, ROC","institution_ids":["https://openalex.org/I4210086894"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085279585","display_name":"Soo\u2010Chang Pei","orcid":"https://orcid.org/0000-0003-2448-4196"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Soo-Chang Pei","raw_affiliation_strings":["Graduate Inst. Comm. Eng., National Taiwan University, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Inst. Comm. Eng., National Taiwan University, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"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/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9624000191688538,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9174000024795532,"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/haar","display_name":"Haar","score":0.7263808846473694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6774254441261292},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5501384139060974},{"id":"https://openalex.org/keywords/haar-wavelet","display_name":"Haar wavelet","score":0.533950924873352},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5162044167518616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49598559737205505},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.48525500297546387},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4416767656803131},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4315341114997864},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4313654601573944},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4297565221786499},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3355143666267395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32302963733673096},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2460063397884369},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.06755492091178894}],"concepts":[{"id":"https://openalex.org/C187029792","wikidata":"https://www.wikidata.org/wiki/Q2179112","display_name":"Haar","level":3,"score":0.7263808846473694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6774254441261292},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5501384139060974},{"id":"https://openalex.org/C2780423554","wikidata":"https://www.wikidata.org/wiki/Q766198","display_name":"Haar wavelet","level":5,"score":0.533950924873352},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5162044167518616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49598559737205505},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.48525500297546387},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4416767656803131},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4315341114997864},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4313654601573944},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4297565221786499},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3355143666267395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32302963733673096},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2460063397884369},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.06755492091178894},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2018.8516987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2018.8516987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1798945469","https://openalex.org/W1902934009","https://openalex.org/W1935978687","https://openalex.org/W1993482030","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2131524184","https://openalex.org/W2132283655","https://openalex.org/W2163605009","https://openalex.org/W2184852195","https://openalex.org/W2267635276","https://openalex.org/W2300242332","https://openalex.org/W2401985367","https://openalex.org/W2546536770","https://openalex.org/W2559813832","https://openalex.org/W2560017826","https://openalex.org/W2604700561","https://openalex.org/W2962835968","https://openalex.org/W2962988160","https://openalex.org/W2963000224","https://openalex.org/W2963048316","https://openalex.org/W2963114950","https://openalex.org/W2963424132","https://openalex.org/W2964118293","https://openalex.org/W2964299589","https://openalex.org/W3118608800","https://openalex.org/W4295262505","https://openalex.org/W4297781745","https://openalex.org/W6637373629","https://openalex.org/W6637551013","https://openalex.org/W6638060716","https://openalex.org/W6639703010","https://openalex.org/W6640289440","https://openalex.org/W6677580257","https://openalex.org/W6679667936","https://openalex.org/W6679755471","https://openalex.org/W6684191040","https://openalex.org/W6685627644","https://openalex.org/W6686418764","https://openalex.org/W6693397755","https://openalex.org/W6698200048","https://openalex.org/W6712771190","https://openalex.org/W6725543821","https://openalex.org/W6730047919","https://openalex.org/W6730093588","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4361795924","https://openalex.org/W2766849256","https://openalex.org/W984746159","https://openalex.org/W1523827626","https://openalex.org/W1999916501","https://openalex.org/W4232769230","https://openalex.org/W2005569824","https://openalex.org/W4239324723","https://openalex.org/W2892809389","https://openalex.org/W1749665274"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2],"has":[3],"revolutionized":[4],"machine":[5],"learning":[6],"recently.":[7],"However,":[8],"it":[9,21],"suffers":[10],"from":[11,53,69],"both":[12],"high":[13],"computation":[14],"and":[15],"memory":[16],"cost":[17],"such":[18,75],"that":[19,47,76,92],"deploying":[20],"on":[22],"a":[23,32,40,49,54,58],"hardware":[24],"with":[25],"limited":[26,101],"resources":[27],"(e.g.,":[28],"mobile":[29],"devices)":[30],"becomes":[31],"challenge.":[33],"To":[34],"address":[35],"this":[36],"problem,":[37],"we":[38,77],"propose":[39],"new":[41],"technique,":[42],"called":[43],"Tensor-Train":[44],"Haar-wavelet":[45,62,73],"decomposition,":[46],"decomposes":[48],"large":[50],"weight":[51],"tensor":[52],"fully-connected":[55],"layer":[56],"into":[57],"sequence":[59],"of":[60,85],"partial":[61,72],"matrices":[63,74],"without":[64,105],"retraining.":[65,106],"The":[66],"novelty":[67],"originates":[68],"the":[70,86],"deterministic":[71],"only":[78],"need":[79],"to":[80],"store":[81],"row":[82],"indices":[83],"instead":[84],"whole":[87],"matrix.":[88],"Empirical":[89],"results":[90],"demonstrate":[91],"our":[93],"method":[94],"achieves":[95],"efficient":[96],"model":[97],"compression":[98],"while":[99],"maintaining":[100],"accuracy":[102],"loss,":[103],"even":[104]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}