{"id":"https://openalex.org/W3012877213","doi":"https://doi.org/10.1109/tsp.2020.3019655","title":"Tune Smarter Not Harder: A Principled Approach to Tuning Learning Rates for Shallow Nets","display_name":"Tune Smarter Not Harder: A Principled Approach to Tuning Learning Rates for Shallow Nets","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3012877213","doi":"https://doi.org/10.1109/tsp.2020.3019655","mag":"3012877213"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2020.3019655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.3019655","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.09844","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039286471","display_name":"Thulasi Tholeti","orcid":"https://orcid.org/0000-0001-7213-9050"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Thulasi Tholeti","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046290878","display_name":"Sheetal Kalyani","orcid":"https://orcid.org/0000-0002-1530-0140"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sheetal Kalyani","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039286471"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":0.1371,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.52925043,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"68","issue":null,"first_page":"5063","last_page":"5078"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9980000257492065,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7050878405570984},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6798530220985413},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5439614057540894},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5364686846733093},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.5017836093902588},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.46077650785446167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45398229360580444},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.4415869414806366},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.43526357412338257},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.4100056290626526},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37457913160324097},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34014052152633667},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19861066341400146},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08575218915939331}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7050878405570984},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6798530220985413},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5439614057540894},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5364686846733093},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.5017836093902588},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.46077650785446167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45398229360580444},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.4415869414806366},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.43526357412338257},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.4100056290626526},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37457913160324097},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34014052152633667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19861066341400146},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08575218915939331},{"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/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2020.3019655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.3019655","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2003.09844","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.09844","pdf_url":"https://arxiv.org/pdf/2003.09844","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.09844","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.09844","pdf_url":"https://arxiv.org/pdf/2003.09844","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":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W60686164","https://openalex.org/W205687800","https://openalex.org/W232880938","https://openalex.org/W583546247","https://openalex.org/W1069790386","https://openalex.org/W1502922572","https://openalex.org/W1514337951","https://openalex.org/W1519060350","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W2000200144","https://openalex.org/W2036038135","https://openalex.org/W2058824758","https://openalex.org/W2097998348","https://openalex.org/W2104762326","https://openalex.org/W2113207845","https://openalex.org/W2126840799","https://openalex.org/W2131241448","https://openalex.org/W2132147894","https://openalex.org/W2146502635","https://openalex.org/W2565516711","https://openalex.org/W2581711117","https://openalex.org/W2592929672","https://openalex.org/W2618398196","https://openalex.org/W2622272405","https://openalex.org/W2739971325","https://openalex.org/W2803522270","https://openalex.org/W2804900738","https://openalex.org/W2807731816","https://openalex.org/W2808958252","https://openalex.org/W2810871807","https://openalex.org/W2883094398","https://openalex.org/W2889153869","https://openalex.org/W2890388200","https://openalex.org/W2902041228","https://openalex.org/W2915097532","https://openalex.org/W2949531572","https://openalex.org/W2962847566","https://openalex.org/W2963035209","https://openalex.org/W2963046563","https://openalex.org/W2963519230","https://openalex.org/W2974468082","https://openalex.org/W3014407784","https://openalex.org/W3035235874","https://openalex.org/W3039984639","https://openalex.org/W4211116959","https://openalex.org/W4285719527","https://openalex.org/W4301283990","https://openalex.org/W6600284362","https://openalex.org/W6608278716","https://openalex.org/W6629804754","https://openalex.org/W6630908557","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6674385629","https://openalex.org/W6677088747","https://openalex.org/W6678911119","https://openalex.org/W6681435938","https://openalex.org/W6732831533","https://openalex.org/W6738373677","https://openalex.org/W6741539563","https://openalex.org/W6751642795","https://openalex.org/W6752544856","https://openalex.org/W6765807149"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W2115072676","https://openalex.org/W4311212821","https://openalex.org/W2045727192","https://openalex.org/W1529660427","https://openalex.org/W2102065768","https://openalex.org/W4390752998","https://openalex.org/W2158578859"],"abstract_inverted_index":{"Effective":[0],"hyper-parameter":[1],"tuning":[2,93],"is":[3,28,60,72,80,104,133],"essential":[4],"to":[5,14,23,48,74,106,135],"guarantee":[6],"the":[7,25,37,41,46,57,76,85,91,120,141,145],"performance":[8],"that":[9,84],"neural":[10,33],"networks":[11],"have":[12],"come":[13],"be":[15,49],"known":[16],"for.In":[17],"this":[18],"work,":[19],"a":[20,63],"principled":[21],"approach":[22],"choosing":[24],"learning":[26,38,138],"rate":[27,39],"proposed":[29,73,86,102],"for":[30],"shallow":[31],"feedforward":[32],"networks.":[34],"We":[35],"associate":[36],"with":[40],"gradient":[42],"Lipschitz":[43],"constant":[44,59],"of":[45,119],"objective":[47],"minimized":[50],"while":[51],"training.":[52],"An":[53],"upper":[54],"bound":[55],"on":[56],"mentioned":[58],"derived,":[61],"and":[62,124,131],"search":[64,87],"algorithm,":[65],"which":[66],"always":[67],"results":[68],"in":[69,114,128],"non-divergent":[70],"traces,":[71],"exploit":[75],"derived":[77],"bound.":[78],"It":[79],"shown":[81,134],"through":[82],"simulations":[83],"method":[88,103],"significantly":[89],"outperforms":[90],"existing":[92,109,142],"methods":[94,143],"such":[95],"as":[96],"Tree":[97],"Parzen":[98],"Estimators":[99],"(TPE).":[100],"The":[101],"applied":[105],"three":[107],"different":[108],"applications:":[110],"a)":[111],"channel":[112],"estimation":[113,127],"OFDM":[115,129],"systems,":[116],"b)":[117],"prediction":[118],"exchange":[121],"currency":[122],"rates,":[123],"c)":[125],"offset":[126],"receivers,":[130],"it":[132],"pick":[136],"better":[137],"rates":[139],"than":[140],"using":[144],"same":[146],"or":[147],"lesser":[148],"compute":[149],"power.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}