{"id":"https://openalex.org/W2069514355","doi":"https://doi.org/10.1109/icassp.2014.6854223","title":"Screening for learning classification rules via Boolean compressed sensing","display_name":"Screening for learning classification rules via Boolean compressed sensing","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2069514355","doi":"https://doi.org/10.1109/icassp.2014.6854223","mag":"2069514355"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6854223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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/A5115590938","display_name":"Sanjeeb Dash","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjeeb Dash","raw_affiliation_strings":["Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","Bus. Analytics & Math. Sci. Dept., IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"Bus. Analytics & Math. Sci. Dept., IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026795227","display_name":"Dmitry Malioutov","orcid":"https://orcid.org/0000-0002-5541-7044"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitry M. Malioutov","raw_affiliation_strings":["Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","Bus. Analytics & Math. Sci. Dept., IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"Bus. Analytics & Math. Sci. Dept., IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015286159","display_name":"Kush R. Varshney","orcid":"https://orcid.org/0000-0002-7376-5536"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kush R. Varshney","raw_affiliation_strings":["Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","Bus. Analytics & Math. Sci. Dept., IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"Bus. Analytics & Math. Sci. Dept., IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2346,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92153866,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"24","issue":null,"first_page":"3360","last_page":"3364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/compressed-sensing","display_name":"Compressed sensing","score":0.7012767195701599},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6164619326591492},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5707786083221436},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5250675082206726},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5091668963432312},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4782228171825409},{"id":"https://openalex.org/keywords/boolean-data-type","display_name":"Boolean data type","score":0.4730609655380249},{"id":"https://openalex.org/keywords/duality","display_name":"Duality (order theory)","score":0.4570983946323395},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4541766345500946},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.369815468788147},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3576735854148865},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3480619192123413},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3115350604057312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29776501655578613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2634398639202118},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.08804738521575928}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7012767195701599},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6164619326591492},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5707786083221436},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5250675082206726},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5091668963432312},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4782228171825409},{"id":"https://openalex.org/C7342684","wikidata":"https://www.wikidata.org/wiki/Q520777","display_name":"Boolean data type","level":2,"score":0.4730609655380249},{"id":"https://openalex.org/C2778023678","wikidata":"https://www.wikidata.org/wiki/Q554403","display_name":"Duality (order theory)","level":2,"score":0.4570983946323395},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4541766345500946},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.369815468788147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3576735854148865},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3480619192123413},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3115350604057312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29776501655578613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2634398639202118},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.08804738521575928},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2014.6854223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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":36,"referenced_works":["https://openalex.org/W112929769","https://openalex.org/W134253518","https://openalex.org/W1543911290","https://openalex.org/W1573785613","https://openalex.org/W1670263352","https://openalex.org/W1989750028","https://openalex.org/W1991532251","https://openalex.org/W2004068811","https://openalex.org/W2097620183","https://openalex.org/W2098902711","https://openalex.org/W2101627389","https://openalex.org/W2106675197","https://openalex.org/W2109562042","https://openalex.org/W2112118326","https://openalex.org/W2112495313","https://openalex.org/W2119667497","https://openalex.org/W2136000097","https://openalex.org/W2155658392","https://openalex.org/W2167580124","https://openalex.org/W2169301591","https://openalex.org/W2170708028","https://openalex.org/W2173497155","https://openalex.org/W3101447189","https://openalex.org/W3103169419","https://openalex.org/W3120740533","https://openalex.org/W4212971335","https://openalex.org/W4234760406","https://openalex.org/W4242286373","https://openalex.org/W4243528505","https://openalex.org/W6604613518","https://openalex.org/W6605501381","https://openalex.org/W6634245187","https://openalex.org/W6674848032","https://openalex.org/W6675863557","https://openalex.org/W6677113535","https://openalex.org/W6684997022"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W2810730439","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2465351041","https://openalex.org/W2000285254"],"abstract_inverted_index":{"Convex":[0],"relaxations":[1],"for":[2,120],"sparse":[3,10,76],"representation":[4],"problems,":[5],"which":[6],"aim":[7],"to":[8,12,41,45],"find":[9],"solutions":[11],"systems":[13,103],"of":[14,20,50,60,93,104,108,127],"equations,":[15],"have":[16],"enabled":[17],"a":[18],"variety":[19],"exciting":[21],"applications":[22],"in":[23,66,111],"high-dimensional":[24],"settings.":[25],"Yet,":[26],"with":[27,102],"dimensions":[28],"large":[29],"enough,":[30],"even":[31],"these":[32],"convex":[33],"formulations":[34],"become":[35],"prohibitively":[36],"expensive.":[37],"Screening":[38],"methods":[39,118],"attempt":[40],"use":[42],"duality":[43],"theory":[44],"dramatically":[46],"reduce":[47,90],"the":[48,51,61,67,91,94,125],"size":[49,92],"optimization":[52],"problem":[53],"through":[54],"easily":[55],"computable":[56],"certificates":[57],"that":[58,87],"many":[59],"variables":[62],"must":[63],"be":[64],"zero":[65],"optimal":[68],"solution.":[69],"In":[70],"this":[71,121],"paper":[72],"we":[73,115],"consider":[74],"learning":[75],"classification":[77,134],"rules":[78,130],"via":[79],"Boolean":[80,98,105],"compressed":[81,99,113],"sensing":[82,100],"and":[83],"develop":[84,116],"screening":[85,117,129],"procedures":[86],"can":[88],"significantly":[89],"resulting":[95],"linear":[96,109],"program.":[97],"deals":[101],"equations":[106,110],"(instead":[107],"traditional":[112],"sensing);":[114],"specifically":[119],"setting.":[122],"We":[123],"demonstrate":[124],"effectiveness":[126],"our":[128],"on":[131],"several":[132],"real-world":[133],"data":[135],"sets.":[136]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
