{"id":"https://openalex.org/W4415124484","doi":"https://doi.org/10.1109/icmlt65785.2025.11193154","title":"Low-Rank Matrix Approximation for Neural Network Compression","display_name":"Low-Rank Matrix Approximation for Neural Network Compression","publication_year":2025,"publication_date":"2025-05-23","ids":{"openalex":"https://openalex.org/W4415124484","doi":"https://doi.org/10.1109/icmlt65785.2025.11193154"},"language":"en","primary_location":{"id":"doi:10.1109/icmlt65785.2025.11193154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193154","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},"type":"conference-paper","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":null,"display_name":"Kalyan Cherukuri","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116845","display_name":"Illinois Mathematics and Science Academy","ror":"https://ror.org/024xf4148","country_code":"US","type":"education","lineage":["https://openalex.org/I4210116845"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kalyan Cherukuri","raw_affiliation_strings":["Kalyan Cherukuri and Aarav Lala are With the Illinois Mathematics and Science Academy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kalyan Cherukuri and Aarav Lala are With the Illinois Mathematics and Science Academy","institution_ids":["https://openalex.org/I4210116845"]}]},{"author_position":"last","author":{"id":null,"display_name":"Aarav Lala","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116845","display_name":"Illinois Mathematics and Science Academy","ror":"https://ror.org/024xf4148","country_code":"US","type":"education","lineage":["https://openalex.org/I4210116845"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aarav Lala","raw_affiliation_strings":["Kalyan Cherukuri and Aarav Lala are With the Illinois Mathematics and Science Academy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kalyan Cherukuri and Aarav Lala are With the Illinois Mathematics and Science Academy","institution_ids":["https://openalex.org/I4210116845"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210116845"],"apc_list":null,"apc_paid":null,"fwci":6.6921,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97201668,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"166","last_page":"170"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.958299994468689,"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":0.958299994468689,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.6898999810218811},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6425999999046326},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.602400004863739},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.49140000343322754},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.46320000290870667},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.43869999051094055},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4372999966144562},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.39160001277923584}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6898999810218811},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6425999999046326},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.602400004863739},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5543000102043152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5307000279426575},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.49140000343322754},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.46320000290870667},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40880000591278076},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.39160001277923584},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.374099999666214},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.3686000108718872},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3603000044822693},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3319000005722046},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C96442724","wikidata":"https://www.wikidata.org/wiki/Q242188","display_name":"Invertible matrix","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C16171025","wikidata":"https://www.wikidata.org/wiki/Q863349","display_name":"Singularity","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.2581999897956848},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2776003309","wikidata":"https://www.wikidata.org/wiki/Q1988072","display_name":"Adaptive algorithm","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlt65785.2025.11193154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193154","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","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":16,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1536680647","https://openalex.org/W1818277846","https://openalex.org/W2040870580","https://openalex.org/W2112796928","https://openalex.org/W2117756735","https://openalex.org/W2134332047","https://openalex.org/W2959070986","https://openalex.org/W3004543888","https://openalex.org/W3020986094","https://openalex.org/W3064585691","https://openalex.org/W3194336675","https://openalex.org/W4285283612","https://openalex.org/W4324057834","https://openalex.org/W4360942255","https://openalex.org/W4385245566"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNNs)":[3],"have":[4],"encountered":[5],"an":[6,61],"emerging":[7],"deployment":[8],"challenge":[9],"due":[10],"to":[11,111],"large":[12],"and":[13,16,107],"expensive":[14],"memory":[15],"computation":[17],"requirements.":[18],"In":[19],"this":[20],"paper,":[21],"we":[22],"present":[23],"a":[24,53,85],"new":[25],"Adaptive-Rank":[26],"Singular":[27],"Value":[28],"Decomposition":[29],"(ARSVD)":[30],"method":[31,96],"that":[32,51,80],"approximates":[33],"the":[34,65,70],"optimal":[35],"rank":[36,66],"for":[37],"compressing":[38],"weight":[39],"matrices":[40],"in":[41],"neural":[42],"networks":[43],"using":[44],"spectral":[45],"entropy.":[46],"Unlike":[47],"conventional":[48],"SVD-based":[49],"methods":[50],"apply":[52],"fixed-rank":[54],"truncation":[55],"across":[56],"all":[57],"layers,":[58],"ARSVD":[59],"uses":[60],"adaptive":[62],"selection":[63],"of":[64,73,88],"per":[67],"layer":[68,82],"through":[69],"entropy":[71],"distribution":[72],"its":[74,89],"singular":[75],"values.":[76],"This":[77],"approach":[78],"ensures":[79],"each":[81],"will":[83],"retain":[84],"certain":[86],"amount":[87],"informational":[90],"content,":[91],"thereby":[92],"reducing":[93],"redundancy.":[94],"Our":[95],"enables":[97],"efficient,":[98],"layer-wise":[99],"compression,":[100],"yielding":[101],"improved":[102],"performance":[103],"with":[104],"reduced":[105],"space":[106],"time":[108],"complexity":[109],"compared":[110],"static-rank":[112],"reduction":[113],"techniques.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-14T00:00:00"}
