{"id":"https://openalex.org/W4372263440","doi":"https://doi.org/10.1109/icassp49357.2023.10094576","title":"Newton-Based Trainable Learning Rate","display_name":"Newton-Based Trainable Learning Rate","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372263440","doi":"https://doi.org/10.1109/icassp49357.2023.10094576"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10094576","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10094576","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"https://openalex.org/A5021130742","display_name":"George Retsinas","orcid":"https://orcid.org/0000-0001-6734-3575"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"George Retsinas","raw_affiliation_strings":["National Technical University of Athens,School of E.C.E.,Athens,Greece,15773"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,School of E.C.E.,Athens,Greece,15773","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039126972","display_name":"Giorgos Sfikas","orcid":"https://orcid.org/0000-0002-7305-2886"},"institutions":[{"id":"https://openalex.org/I4210094138","display_name":"University of West Attica","ror":"https://ror.org/00r2r5k05","country_code":"GR","type":"education","lineage":["https://openalex.org/I4210094138"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Giorgos Sfikas","raw_affiliation_strings":["University of West Attica,Dept. of Surveying & Geoinformatics Engineering,Athens,Greece,12243"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of West Attica,Dept. of Surveying & Geoinformatics Engineering,Athens,Greece,12243","institution_ids":["https://openalex.org/I4210094138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025430640","display_name":"Panagiotis P. Filntisis","orcid":"https://orcid.org/0000-0002-2042-245X"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Panagiotis Paraskevas Filntisis","raw_affiliation_strings":["National Technical University of Athens,School of E.C.E.,Athens,Greece,15773"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,School of E.C.E.,Athens,Greece,15773","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079243420","display_name":"Petros Maragos","orcid":"https://orcid.org/0000-0003-0534-2707"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Petros Maragos","raw_affiliation_strings":["National Technical University of Athens,School of E.C.E.,Athens,Greece,15773"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,School of E.C.E.,Athens,Greece,15773","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.03867987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9991999864578247,"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":0.7541342377662659},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.6919975876808167},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.603647768497467},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5732146501541138},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5269903540611267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48171931505203247},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.48068055510520935},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46206578612327576},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.41825318336486816},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.41479191184043884},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3604923486709595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1441054344177246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7541342377662659},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.6919975876808167},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.603647768497467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5732146501541138},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5269903540611267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48171931505203247},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.48068055510520935},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46206578612327576},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.41825318336486816},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.41479191184043884},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3604923486709595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1441054344177246},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10094576","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10094576","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W24696228","https://openalex.org/W221209143","https://openalex.org/W1522301498","https://openalex.org/W1811750039","https://openalex.org/W2014851363","https://openalex.org/W2076605490","https://openalex.org/W2117539524","https://openalex.org/W2129142203","https://openalex.org/W2146502635","https://openalex.org/W2194775991","https://openalex.org/W2411124016","https://openalex.org/W2622263826","https://openalex.org/W2625885504","https://openalex.org/W2776855315","https://openalex.org/W2899748887","https://openalex.org/W2936995161","https://openalex.org/W2952086041","https://openalex.org/W2963075511","https://openalex.org/W2963263347","https://openalex.org/W2963842222","https://openalex.org/W2964054038","https://openalex.org/W2964137095","https://openalex.org/W2970028551","https://openalex.org/W3003249520","https://openalex.org/W3046782701","https://openalex.org/W3118608800","https://openalex.org/W3208237615","https://openalex.org/W4221163212","https://openalex.org/W4286891340","https://openalex.org/W4287864992","https://openalex.org/W4293402910","https://openalex.org/W4301014524","https://openalex.org/W6631190155","https://openalex.org/W6638214083","https://openalex.org/W6681435938","https://openalex.org/W6713132643","https://openalex.org/W6714806974","https://openalex.org/W6726497184","https://openalex.org/W6735487127","https://openalex.org/W6739170280","https://openalex.org/W6739622702","https://openalex.org/W6747043858","https://openalex.org/W6748026067","https://openalex.org/W6759546789","https://openalex.org/W6761030284","https://openalex.org/W6762875675","https://openalex.org/W6774569997","https://openalex.org/W6787972765","https://openalex.org/W6810088914"],"related_works":["https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668","https://openalex.org/W3008318776","https://openalex.org/W2041416246","https://openalex.org/W3020853991","https://openalex.org/W3035836947"],"abstract_inverted_index":{"Selecting":[0],"an":[1,39,133],"appropriate":[2],"learning":[3,45,65,81,123],"rate":[4,46,66,82,124],"for":[5,41,105,132],"efficiently":[6],"training":[7,49],"deep":[8],"neural":[9],"networks":[10],"is":[11,61],"a":[12,52,91,106],"difficult":[13],"process":[14],"that":[15],"can":[16],"be":[17,117],"affected":[18],"by":[19],"numerous":[20],"parameters,":[21],"such":[22],"as":[23,83],"the":[24,26,31,44,48,64,69,80,99,102,121,126],"dataset,":[25],"model":[27,70],"architecture":[28],"or":[29],"even":[30],"batch":[32,127],"size.":[33],"In":[34],"this":[35],"work,":[36],"we":[37,73],"propose":[38],"algorithm":[40],"automatically":[42],"adjusting":[43],"during":[47],"process,":[50],"assuming":[51],"gradient":[53],"descent":[54],"formulation.":[55],"The":[56,111],"rationale":[57],"behind":[58],"our":[59],"approach":[60],"to":[62,90,116,119],"train":[63],"along":[67],"with":[68],"weights.":[71],"Specifically,":[72],"formulate":[74],"first":[75],"and":[76,125],"second-order":[77],"gradients":[78],"w.r.t.":[79],"functions":[84],"of":[85,101,108],"consecutive":[86],"weight":[87],"gradients,":[88],"leading":[89],"cost-effective":[92],"implementation.":[93],"Our":[94],"extensive":[95],"experimental":[96],"evaluation":[97],"validates":[98],"effectiveness":[100],"proposed":[103,112],"method":[104,113],"plethora":[107],"different":[109],"settings.":[110],"has":[114],"proven":[115],"robust":[118],"both":[120],"initial":[122],"size,":[128],"making":[129],"it":[130],"ideal":[131],"off-the-shelf":[134],"optimizing":[135],"scheme.":[136]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}