{"id":"https://openalex.org/W4401692559","doi":"https://doi.org/10.1109/isit57864.2024.10619386","title":"Benefits of Stochastic Mirror Descent in High-Dimensional Binary Classification","display_name":"Benefits of Stochastic Mirror Descent in High-Dimensional Binary Classification","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4401692559","doi":"https://doi.org/10.1109/isit57864.2024.10619386"},"language":"en","primary_location":{"id":"doi:10.1109/isit57864.2024.10619386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit57864.2024.10619386","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"article","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/A5003605323","display_name":"K. N. V. Suresh Varma","orcid":null},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K Nithin Varma","raw_affiliation_strings":["California Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California Institute of Technology","institution_ids":["https://openalex.org/I122411786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002430773","display_name":"Babak Hassibi","orcid":"https://orcid.org/0000-0002-1375-5838"},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Babak Hassibi","raw_affiliation_strings":["California Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California Institute of Technology","institution_ids":["https://openalex.org/I122411786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2187,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49175436,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"196","last_page":"201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.5920000076293945,"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/T10057","display_name":"Face and Expression Recognition","score":0.5920000076293945,"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/T10320","display_name":"Neural Networks and Applications","score":0.5472999811172485,"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":0.4936000108718872,"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/binary-number","display_name":"Binary number","score":0.708486020565033},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.6127684712409973},{"id":"https://openalex.org/keywords/descent","display_name":"Descent (aeronautics)","score":0.595645546913147},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5769256353378296},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.45316827297210693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42604708671569824},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3589264750480652},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2768440246582031},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1353147327899933},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11030998826026917},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.10900190472602844},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.06151416897773743}],"concepts":[{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.708486020565033},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.6127684712409973},{"id":"https://openalex.org/C2776637919","wikidata":"https://www.wikidata.org/wiki/Q624380","display_name":"Descent (aeronautics)","level":2,"score":0.595645546913147},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5769256353378296},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.45316827297210693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42604708671569824},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3589264750480652},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2768440246582031},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1353147327899933},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11030998826026917},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.10900190472602844},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.06151416897773743},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit57864.2024.10619386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit57864.2024.10619386","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Information Theory (ISIT)","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":46,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W590507843","https://openalex.org/W1505731132","https://openalex.org/W1994616650","https://openalex.org/W2040745222","https://openalex.org/W2566079294","https://openalex.org/W2922153390","https://openalex.org/W2923764619","https://openalex.org/W2938247478","https://openalex.org/W2940068490","https://openalex.org/W2960643108","https://openalex.org/W2963017107","https://openalex.org/W2963131734","https://openalex.org/W2963826371","https://openalex.org/W2964047251","https://openalex.org/W3005981462","https://openalex.org/W3014316192","https://openalex.org/W3015508253","https://openalex.org/W3018252856","https://openalex.org/W3020361330","https://openalex.org/W3093568497","https://openalex.org/W3105792944","https://openalex.org/W3157298807","https://openalex.org/W3202433451","https://openalex.org/W4221148450","https://openalex.org/W4281824924","https://openalex.org/W4287777768","https://openalex.org/W4288334315","https://openalex.org/W4295132142","https://openalex.org/W4386066341","https://openalex.org/W6617492364","https://openalex.org/W6623408330","https://openalex.org/W6637422517","https://openalex.org/W6748155593","https://openalex.org/W6752125765","https://openalex.org/W6752591435","https://openalex.org/W6763427118","https://openalex.org/W6765643347","https://openalex.org/W6776071938","https://openalex.org/W6777730395","https://openalex.org/W6779356556","https://openalex.org/W6779553403","https://openalex.org/W6779785666","https://openalex.org/W6783911279","https://openalex.org/W6810567194","https://openalex.org/W6838477436"],"related_works":["https://openalex.org/W2486267010","https://openalex.org/W4298096494","https://openalex.org/W1678820847","https://openalex.org/W2559216629","https://openalex.org/W1553684505","https://openalex.org/W1607707911","https://openalex.org/W2037211941","https://openalex.org/W2042403445","https://openalex.org/W2725816051","https://openalex.org/W3113922403"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,23,44,51,60,81,93,96,125],"precise":[3],"asymptotic":[4],"behavior":[5],"of":[6,35,80,92,95,128],"stochastic":[7],"mirror":[8],"descent":[9],"(SMD)":[10],"algorithms":[11],"in":[12,55,123,135],"over-parameterized":[13,21],"binary":[14],"linear":[15],"classification":[16],"using":[17],"regression.":[18],"In":[19,83],"this":[20,84],"regime,":[22],"training":[24],"loss":[25],"has":[26,65],"infinitely":[27],"many":[28],"global":[29],"minima":[30],"which":[31],"defines":[32],"a":[33,107],"manifold":[34],"interpolating":[36,45],"solutions.":[37],"SMD":[38,129],"exhibits":[39],"implicit":[40],"regularization":[41],"and":[42,77,98,119],"finds":[43],"solution":[46,97],"that":[47,69],"is":[48],"closest":[49],"to":[50,59,73],"initial":[52],"weight":[53],"vector":[54],"Bregman":[56],"divergence":[57],"(corresponding":[58],"mirror's":[61],"potential":[62],"function).":[63],"It":[64],"been":[66],"empirically":[67],"observed":[68],"different":[70,74,78],"potentials":[71],"lead":[72],"generalization":[75,101,126],"errors":[76],"distributions":[79],"weights.":[82],"paper,":[85],"we":[86],"explicitly":[87],"compute":[88],"closed":[89],"form":[90],"expressions":[91],"distribution":[94],"characterise":[99],"its":[100],"performance":[102,127],"on":[103,130],"data":[104],"generated":[105],"by":[106],"Gaussian":[108],"Mixture":[109],"model":[110],"(GMM).":[111],"The":[112],"theory":[113],"presented":[114],"well":[115],"matches":[116],"empirical":[117],"simulations":[118],"can":[120],"provide":[121],"insights":[122],"understanding":[124],"nonlinear":[131],"models,":[132],"such":[133],"as":[134],"deep":[136],"learning.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
