{"id":"https://openalex.org/W2925291349","doi":"https://doi.org/10.1109/isit.2019.8849836","title":"Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression","display_name":"Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2925291349","doi":"https://doi.org/10.1109/isit.2019.8849836","mag":"2925291349"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2019.8849836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2019.8849836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"preprint","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/A5000907904","display_name":"Hong Hu","orcid":"https://orcid.org/0000-0002-5162-0459"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hong Hu","raw_affiliation_strings":["John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA","John\u2005A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA"],"affiliations":[{"raw_affiliation_string":"John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"John\u2005A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038111389","display_name":"Yue M. Lu","orcid":"https://orcid.org/0000-0002-5174-2595"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue M. Lu","raw_affiliation_strings":["John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA","John\u2005A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA"],"affiliations":[{"raw_affiliation_string":"John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"John\u2005A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000907904"],"corresponding_institution_ids":["https://openalex.org/I136199984"],"apc_list":null,"apc_paid":null,"fwci":0.3868,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57768206,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"375","last_page":"379"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9641000032424927,"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/regularization","display_name":"Regularization (linguistics)","score":0.7430403828620911},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7123163938522339},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6690895557403564},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6500870585441589},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.637765645980835},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5299088954925537},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5126668214797974},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.49351227283477783},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4921683669090271},{"id":"https://openalex.org/keywords/elastic-net-regularization","display_name":"Elastic net regularization","score":0.49078473448753357},{"id":"https://openalex.org/keywords/asymptotically-optimal-algorithm","display_name":"Asymptotically optimal algorithm","score":0.4907701909542084},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4596066474914551},{"id":"https://openalex.org/keywords/optimal-design","display_name":"Optimal design","score":0.4310798645019531},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.43096548318862915},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4165041148662567},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4121701121330261},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.40496009588241577},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.19204801321029663},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16978934407234192},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08247530460357666}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7430403828620911},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7123163938522339},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6690895557403564},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6500870585441589},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.637765645980835},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5299088954925537},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5126668214797974},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.49351227283477783},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4921683669090271},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.49078473448753357},{"id":"https://openalex.org/C181789720","wikidata":"https://www.wikidata.org/wiki/Q4812191","display_name":"Asymptotically optimal algorithm","level":2,"score":0.4907701909542084},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4596066474914551},{"id":"https://openalex.org/C186394612","wikidata":"https://www.wikidata.org/wiki/Q7098942","display_name":"Optimal design","level":2,"score":0.4310798645019531},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.43096548318862915},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4165041148662567},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4121701121330261},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.40496009588241577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.19204801321029663},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16978934407234192},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08247530460357666},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isit.2019.8849836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2019.8849836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},{"id":"mag:2925291349","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1916786071","https://openalex.org/W2082074261","https://openalex.org/W2123202508","https://openalex.org/W2962710557","https://openalex.org/W2963017107","https://openalex.org/W2963696951","https://openalex.org/W2963787255","https://openalex.org/W2963943067","https://openalex.org/W6623408330","https://openalex.org/W6690044205","https://openalex.org/W6717170449"],"related_works":["https://openalex.org/W3003286839","https://openalex.org/W2222311485","https://openalex.org/W2942271371","https://openalex.org/W3081533301","https://openalex.org/W2897282591","https://openalex.org/W3123253824","https://openalex.org/W1716904016","https://openalex.org/W2895923283","https://openalex.org/W2261684225","https://openalex.org/W3102897257","https://openalex.org/W2924534955","https://openalex.org/W2888738034","https://openalex.org/W2951063292","https://openalex.org/W2078335586","https://openalex.org/W2950226926","https://openalex.org/W2289220458","https://openalex.org/W2522055410","https://openalex.org/W2963086989","https://openalex.org/W2053243391","https://openalex.org/W2756886357"],"abstract_inverted_index":{"In":[0,19,81],"sparse":[1],"linear":[2],"regression,":[3],"the":[4,17,29,34,38,47,64,69,87,115,130],"SLOPE":[5,32],"estimator":[6],"generalizes":[7],"LASSO":[8,122],"by":[9],"assigning":[10],"magnitude-dependent":[11],"regularizations":[12],"to":[13,46,56,61,67],"different":[14],"coordinates":[15],"of":[16,28,31,40,49,78,117],"estimate.":[18],"this":[20],"paper,":[21],"we":[22,84],"present":[23],"an":[24],"asymptotically":[25],"exact":[26],"characterization":[27,53],"performance":[30],"in":[33,44,71,129],"high-dimensional":[35],"regime":[36],"where":[37],"number":[39,48],"unknown":[41],"parameters":[42],"grows":[43],"proportion":[45],"observations.":[50],"Our":[51],"asymptotic":[52,110],"enables":[54],"us":[55],"derive":[57],"optimal":[58,88,119],"regularization":[59,125],"sequences":[60],"either":[62],"minimize":[63],"MSE":[65],"or":[66],"maximize":[68],"power":[70],"variable":[72],"selection":[73],"under":[74],"any":[75],"given":[76],"level":[77],"Type-I":[79],"error.":[80],"both":[82],"cases,":[83],"show":[85],"that":[86],"design":[89,120],"can":[90],"be":[91],"recast":[92],"as":[93],"certain":[94],"infinite-dimensional":[95],"convex":[96],"optimization":[97],"problems,":[98],"which":[99],"have":[100],"efficient":[101],"and":[102,123],"accurate":[103],"finite-dimensional":[104],"approximations.":[105],"Numerical":[106],"simulations":[107],"verify":[108],"our":[109,118],"predictions.":[111],"They":[112],"also":[113],"demonstrate":[114],"superiority":[116],"over":[121],"a":[124],"sequence":[126],"previously":[127],"proposed":[128],"literature.":[131]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}