{"id":"https://openalex.org/W4380993692","doi":"https://doi.org/10.48550/arxiv.2306.08590","title":"Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning","display_name":"Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning","publication_year":2023,"publication_date":"2023-06-14","ids":{"openalex":"https://openalex.org/W4380993692","doi":"https://doi.org/10.48550/arxiv.2306.08590"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2306.08590","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.08590","pdf_url":"https://arxiv.org/pdf/2306.08590","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.08590","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102775428","display_name":"Nikhil Vyas","orcid":"https://orcid.org/0000-0002-4055-7693"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vyas, Nikhil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086429101","display_name":"Depen Morwani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morwani, Depen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088011506","display_name":"Rosie Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Rosie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018206582","display_name":"Gal Kaplun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaplun, Gal","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108381794","display_name":"Sham M. Kakade","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kakade, Sham","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102710346","display_name":"Boaz Barak","orcid":"https://orcid.org/0000-0002-4053-8927"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barak, Boaz","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102775428"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9962000250816345,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9962000250816345,"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/T12676","display_name":"Machine Learning and ELM","score":0.980400025844574,"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/T10320","display_name":"Neural Networks and Applications","score":0.9510999917984009,"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/computer-science","display_name":"Computer science","score":0.6565926671028137},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6341599822044373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5615468621253967},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5035452246665955},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.4825253188610077},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.47846221923828125},{"id":"https://openalex.org/keywords/offline-learning","display_name":"Offline learning","score":0.42348712682724},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.4169148802757263},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.131577730178833},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.09265497326850891},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08922860026359558}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6565926671028137},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6341599822044373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5615468621253967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5035452246665955},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.4825253188610077},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.47846221923828125},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.42348712682724},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.4169148802757263},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.131577730178833},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.09265497326850891},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08922860026359558},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2306.08590","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.08590","pdf_url":"https://arxiv.org/pdf/2306.08590","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.08590","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.08590","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2306.08590","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.08590","pdf_url":"https://arxiv.org/pdf/2306.08590","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5199999809265137,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1264789558","display_name":null,"funder_award_id":"W911NF2010021","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G2078244491","display_name":null,"funder_award_id":"W911NF201002","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G2906497980","display_name":null,"funder_award_id":"DMS-213415","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3521671702","display_name":null,"funder_award_id":"2134157","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4720003262","display_name":null,"funder_award_id":"N00014-22","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G5224039946","display_name":null,"funder_award_id":"DE-SC0022199","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G5877837315","display_name":null,"funder_award_id":"DE-SC0022199","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8881845055","display_name":"AF: Medium: Collaborative Research: Estimation, Learning, and Memory: The Quest for Statistically Optimal Algorithms","funder_award_id":"2212841","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4380993692.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W143502885","https://openalex.org/W42113618","https://openalex.org/W2103468410","https://openalex.org/W1856228368","https://openalex.org/W2480115405","https://openalex.org/W4386715814","https://openalex.org/W2952181314","https://openalex.org/W3207447243","https://openalex.org/W3144950473","https://openalex.org/W3133629861"],"abstract_inverted_index":{"The":[0],"success":[1],"of":[2,38,52,80,113,138],"SGD":[3,39,81,97,139],"in":[4,70,83,98,127,147],"deep":[5],"learning":[6,30,85],"has":[7],"been":[8],"ascribed":[9],"by":[10,18],"prior":[11,25],"works":[12,26],"to":[13,75],"the":[14,36,78,99,110,114,135],"implicit":[15,67],"bias":[16,68],"induced":[17],"finite":[19],"batch":[20,61],"sizes":[21,62],"(\"SGD":[22],"noise\").":[23],"While":[24],"focused":[27],"on":[28,41],"offline":[29,76],"(i.e.,":[31,43],"multiple-epoch":[32],"training),":[33],"we":[34,57],"study":[35,120],"impact":[37],"noise":[40,82],"online":[42,71,84,100,148],"single":[44],"epoch)":[45],"learning.":[46,72,149],"Through":[47],"an":[48],"extensive":[49],"empirical":[50],"analysis":[51],"image":[53],"and":[54,123,129,140],"language":[55],"data,":[56],"demonstrate":[58],"that":[59,96],"small":[60],"do":[63],"not":[64],"confer":[65],"any":[66],"advantages":[69],"In":[73],"contrast":[74],"learning,":[77],"benefits":[79],"are":[86],"strictly":[87],"computational,":[88],"facilitating":[89],"more":[90],"cost-effective":[91],"gradient":[92,116],"steps.":[93],"This":[94],"suggests":[95],"regime":[101],"can":[102],"be":[103],"construed":[104],"as":[105],"taking":[106],"noisy":[107],"steps":[108],"along":[109],"\"golden":[111],"path\"":[112],"noiseless":[115],"descent":[117],"algorithm.":[118],"We":[119],"this":[121],"hypothesis":[122],"provide":[124],"supporting":[125],"evidence":[126],"loss":[128],"function":[130],"space.":[131],"Our":[132],"findings":[133],"challenge":[134],"prevailing":[136],"understanding":[137],"offer":[141],"novel":[142],"insights":[143],"into":[144],"its":[145],"role":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
