{"id":"https://openalex.org/W2141104339","doi":null,"title":"Periodic Step Size Adaptation for Single Pass On-line Learning","display_name":"Periodic Step Size Adaptation for Single Pass On-line Learning","publication_year":2009,"publication_date":"2009-12-07","ids":{"openalex":"https://openalex.org/W2141104339","mag":"2141104339"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.214.9128","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.9128","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://books.nips.cc/papers/files/nips22/NIPS2009_1160.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5040580626","display_name":"Chun\u2010Nan Hsu","orcid":"https://orcid.org/0000-0002-5240-4707","observed_orcids":["https://orcid.org/0000-0002-5240-4707"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"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"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW","US"],"is_corresponding":false,"raw_author_name":"Chun\u2010Nan Hsu","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Taipei, Taiwan and USC/Information Sciences Institute, Marina del Rey, CA#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-5240-4707","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taipei, Taiwan and USC/Information Sciences Institute, Marina del Rey, CA#TAB#","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I4210098366","https://openalex.org/I84653119"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104172512","display_name":"Yu-Ming Chang","orcid":null,"observed_orcids":[]},"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"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Ming Chang","raw_affiliation_strings":["Institute of Information Science,Academia Sinica,,Taipei,,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science,Academia Sinica,,Taipei,,Taiwan","institution_ids":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027210768","display_name":"Han-Shen Huang","orcid":null,"observed_orcids":[]},"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"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Han-Shen Huang","raw_affiliation_strings":["Institute of Information Science,Academia Sinica,,Taipei,,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science,Academia Sinica,,Taipei,,Taiwan","institution_ids":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038395989","display_name":"Yuh\u2010Jye Lee","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yuh\u2010Jye Lee","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.#TAB#","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3295,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64331614,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"763","last_page":"771"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9994999766349792,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9994999766349792,"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":9.999999747378752e-05,"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/T12535","display_name":"Machine Learning and Data Classification","score":9.999999747378752e-05,"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/hessian-approximation","display_name":"Hessian approximation","score":0.9179999828338623},{"id":"https://openalex.org/keywords/hessian-free-optimization","display_name":"Hessian-free optimization","score":0.597000002861023},{"id":"https://openalex.org/keywords/generalization-performance","display_name":"generalization performance","score":0.5070000290870667}],"concepts":[{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.9543692469596863},{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.8647202849388123},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6420224905014038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5584398508071899},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.49020177125930786},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.47183850407600403},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45382416248321533},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.44190773367881775},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4357983469963074},{"id":"https://openalex.org/C85522705","wikidata":"https://www.wikidata.org/wiki/Q3278015","display_name":"Line search","level":3,"score":0.422194242477417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40934139490127563},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.408966064453125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2309272289276123},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.17026466131210327},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11112716794013977},{"id":"https://openalex.org/C178635117","wikidata":"https://www.wikidata.org/wiki/Q747499","display_name":"RADIUS","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.214.9128","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.9128","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://books.nips.cc/papers/files/nips22/NIPS2009_1160.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.597.9203","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.597.9203","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.iis.sinica.edu.tw/~chunnan/DOWNLOADS/n09f.pdf","raw_type":"text"},{"id":"mag:2141104339","doi":null,"is_oa":false,"landing_page_url":"http://books.nips.cc/papers/files/nips22/NIPS2009_1160.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1568229137","https://openalex.org/W2035720976","https://openalex.org/W2068556706","https://openalex.org/W2101159990","https://openalex.org/W2102547221","https://openalex.org/W2109189215","https://openalex.org/W2111284535","https://openalex.org/W2112796928","https://openalex.org/W2113651538","https://openalex.org/W2114361266","https://openalex.org/W2123740206","https://openalex.org/W2142623206","https://openalex.org/W2150024778","https://openalex.org/W2153635508","https://openalex.org/W2156515921","https://openalex.org/W2164273299","https://openalex.org/W2208938455","https://openalex.org/W2914484425","https://openalex.org/W3029645440","https://openalex.org/W3082731548"],"related_works":["https://openalex.org/W7096279033","https://openalex.org/W2102547221","https://openalex.org/W4297806687","https://openalex.org/W1705748131","https://openalex.org/W7133197042","https://openalex.org/W4221145026","https://openalex.org/W7097643014","https://openalex.org/W3169709194","https://openalex.org/W4415798318","https://openalex.org/W3035359320"],"abstract_inverted_index":{"It":[0],"has":[1],"been":[2],"established":[3],"that":[4],"the":[5,29,36,39,43,59,63,72,78],"second-order":[6],"stochastic":[7],"gradient":[8],"descent":[9],"(2SGD)":[10],"method":[11],"can":[12],"potentially":[13],"achieve":[14,82],"generalization":[15],"performance":[16],"as":[17,19],"well":[18],"empirical":[20],"optimum":[21],"in":[22,85],"a":[23,68,88],"single":[24],"pass":[25],"(i.e.,":[26],"epoch)":[27],"through":[28],"training":[30],"examples.":[31],"However,":[32],"2SGD":[33],"requires":[34],"computing":[35],"inverse":[37],"of":[38,42,62,91],"Hessian":[40,75,79],"matrix":[41,61],"loss":[44],"function,":[45],"which":[46,57],"is":[47],"prohibitively":[48],"expensive.":[49],"This":[50],"paper":[51],"presents":[52],"Periodic":[53],"Step-size":[54],"Adapta-tion":[55],"(PSA),":[56],"approximates":[58],"Jacobian":[60,73],"mapping":[64],"function":[65],"and":[66,74,81,93],"explores":[67],"linear":[69],"relation":[70],"between":[71],"to":[76],"approximate":[77],"periodically":[80],"near-optimal":[83],"results":[84],"experiments":[86],"on":[87],"wide":[89],"variety":[90],"models":[92],"tasks.":[94],"1":[95]},"counts_by_year":[],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2016-06-24T00:00:00"}
