{"id":"https://openalex.org/W3035149722","doi":"https://doi.org/10.5555/2789272.2912110","title":"The sample complexity of learning linear predictors with the squared loss","display_name":"The sample complexity of learning linear predictors with the squared loss","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W3035149722","doi":"https://doi.org/10.5555/2789272.2912110","mag":"3035149722"},"language":"en","primary_location":{"id":"mag:3035149722","is_oa":false,"landing_page_url":"https://dl.acm.org/doi/10.5555/2789272.2912110","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research","raw_type":null},"type":"article","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/A5011200077","display_name":"ShamirOhad","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"ShamirOhad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5011200077"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27278718,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.996999979019165,"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/sample-complexity","display_name":"Sample complexity","score":0.7185633182525635},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.602586030960083},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5426121950149536},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5326252579689026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4928310215473175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4353828728199005},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.42948031425476074},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4143053889274597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35980886220932007},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3410276472568512},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3058319687843323},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.05913740396499634}],"concepts":[{"id":"https://openalex.org/C2778445095","wikidata":"https://www.wikidata.org/wiki/Q18354077","display_name":"Sample complexity","level":2,"score":0.7185633182525635},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.602586030960083},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5426121950149536},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5326252579689026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4928310215473175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4353828728199005},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.42948031425476074},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4143053889274597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35980886220932007},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3410276472568512},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3058319687843323},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.05913740396499634},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3035149722","is_oa":false,"landing_page_url":"https://dl.acm.org/doi/10.5555/2789272.2912110","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Journal of Machine Learning Research","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2886809461","https://openalex.org/W2081668314","https://openalex.org/W2745783318","https://openalex.org/W3124715297","https://openalex.org/W2963304125","https://openalex.org/W3153314569","https://openalex.org/W3011950302","https://openalex.org/W3206964138","https://openalex.org/W3122629389","https://openalex.org/W3021707751","https://openalex.org/W2129467386","https://openalex.org/W2081983677","https://openalex.org/W3122244600","https://openalex.org/W2272001694","https://openalex.org/W3148524960","https://openalex.org/W1587868422","https://openalex.org/W3002472375","https://openalex.org/W1998306399","https://openalex.org/W2314066266","https://openalex.org/W1963525310"],"abstract_inverted_index":{"We":[0],"provide":[1],"a":[2],"tight":[3],"sample":[4],"complexity":[5],"bound":[6],"for":[7],"learning":[8],"bounded-norm":[9],"linear":[10],"predictors":[11],"with":[12],"respect":[13],"to":[14],"the":[15],"squared":[16],"loss.":[17],"Our":[18],"focus":[19],"is":[20],"on":[21],"an":[22],"agnostic":[23],"PAC-style":[24],"setting,":[25],"where":[26],"no":[27],"assumptions":[28],"are":[29],"made...":[30]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-10-10T17:16:08.811792","created_date":"2025-10-10T00:00:00"}
