{"id":"https://openalex.org/W4226292399","doi":"https://doi.org/10.1109/tit.2022.3169998","title":"Sufficiently Informative and Relevant Features: An Information-Theoretic and Fourier-Based Characterization","display_name":"Sufficiently Informative and Relevant Features: An Information-Theoretic and Fourier-Based Characterization","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4226292399","doi":"https://doi.org/10.1109/tit.2022.3169998"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2022.3169998","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2022.3169998","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-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/A5057495936","display_name":"Mohsen Heidari","orcid":"https://orcid.org/0000-0002-0012-2900"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohsen Heidari","raw_affiliation_strings":["Computer Science Department, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-0012-2900","affiliations":[{"raw_affiliation_string":"Computer Science Department, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000657571","display_name":"Jithin K. Sreedharan","orcid":"https://orcid.org/0000-0003-4209-2065"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jithin K. Sreedharan","raw_affiliation_strings":["Computer Science and Engineering Department, Indian Institute of Technology Kanpur, Kanpur, India"],"raw_orcid":"https://orcid.org/0000-0003-4209-2065","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Indian Institute of Technology Kanpur, Kanpur, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072780983","display_name":"Gil I. Shamir","orcid":"https://orcid.org/0000-0002-4307-9180"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gil Shamir","raw_affiliation_strings":["Google Inc, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4307-9180","affiliations":[{"raw_affiliation_string":"Google Inc, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019536160","display_name":"Wojciech Szpankowski","orcid":"https://orcid.org/0000-0001-9062-0067"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wojciech Szpankowski","raw_affiliation_strings":["Computer Science Department, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-9062-0067","affiliations":[{"raw_affiliation_string":"Computer Science Department, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057495936"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.3061,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53060031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"68","issue":"9","first_page":"6063","last_page":"6077"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"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":0.9988999962806702,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9986000061035156,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9977999925613403,"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/feature-selection","display_name":"Feature selection","score":0.6677568554878235},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5230284929275513},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5159667134284973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.505122721195221},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4948357939720154},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4839251637458801},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4759497344493866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43087780475616455},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3726666271686554}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6677568554878235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5230284929275513},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5159667134284973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.505122721195221},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4948357939720154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4839251637458801},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4759497344493866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43087780475616455},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3726666271686554},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2022.3169998","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2022.3169998","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309327","display_name":"Google","ror":"https://ror.org/00njsd438"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W141062567","https://openalex.org/W190437827","https://openalex.org/W1638081485","https://openalex.org/W1849729440","https://openalex.org/W2017337590","https://openalex.org/W2040884411","https://openalex.org/W2063003848","https://openalex.org/W2065015368","https://openalex.org/W2099111195","https://openalex.org/W2099294566","https://openalex.org/W2104793053","https://openalex.org/W2118561568","https://openalex.org/W2128873747","https://openalex.org/W2149620660","https://openalex.org/W2149772057","https://openalex.org/W2154053567","https://openalex.org/W2156571267","https://openalex.org/W2171837816","https://openalex.org/W2260771218","https://openalex.org/W2295021037","https://openalex.org/W2474269906","https://openalex.org/W2478708596","https://openalex.org/W2508764751","https://openalex.org/W2727102647","https://openalex.org/W2759445433","https://openalex.org/W2905061379","https://openalex.org/W2911627187","https://openalex.org/W2943958448","https://openalex.org/W2964075504","https://openalex.org/W2975218903","https://openalex.org/W2995161752","https://openalex.org/W2998216295","https://openalex.org/W3102754027","https://openalex.org/W3105524694","https://openalex.org/W3120740533","https://openalex.org/W4234552994","https://openalex.org/W4237125310","https://openalex.org/W6607693206","https://openalex.org/W6638875480","https://openalex.org/W6675723100","https://openalex.org/W6681822384","https://openalex.org/W6682904970","https://openalex.org/W6692628530","https://openalex.org/W6739891508","https://openalex.org/W6744763236","https://openalex.org/W6771688297","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W4307883119","https://openalex.org/W2345184372","https://openalex.org/W2374344280","https://openalex.org/W2546942002","https://openalex.org/W2159220931","https://openalex.org/W27971500","https://openalex.org/W2316780152","https://openalex.org/W2554403468","https://openalex.org/W2592385986","https://openalex.org/W1563079527"],"abstract_inverted_index":{"A":[0],"fundamental":[1],"challenge":[2],"in":[3,13,28,34,180],"learning":[4,85,148],"is":[5,60],"the":[6,14,35,39,64,69,91,102,107,120,130,172,181,185,190,196],"presence":[7],"of":[8,38,54,63,80,94],"nonlinear":[9,205],"redundancies":[10,100,143],"and":[11,31,105,112,124,144,157,160,177,246],"dependencies":[12],"data.":[15],"To":[16],"address":[17],"this,":[18],"we":[19,83,97,115,136,170,193,209,223,238],"propose":[20,137],"a":[21,44,61,117,138,200,211,220],"Fourier-based":[22],"approach":[23],"to":[24,119,140,203],"characterize":[25,98,204],"feature":[26,87,99,142,166,174,235,256],"redundancies,":[27],"unsupervised":[29,92,147,165],"learning,":[30],"feature-label":[32,206],"dependencies,":[33],"supervised":[36,173,255],"variant":[37,93],"problem.":[40],"We":[41,150],"first":[42],"develop":[43],"novel":[45],"Fourier":[46,66,122,182,191,197],"expansion":[47,67,123,198],"for":[48,215],"functions":[49],"(more":[50],"generally":[51],"stochastic":[52],"mappings)":[53],"correlated":[55],"binary":[56],"random":[57],"variables.":[58],"This":[59],"generalization":[62],"standard":[65],"on":[68,129,134,154,163,243,253],"Boolean":[70],"cube":[71],"beyond":[72],"product":[73],"probability":[74],"spaces.":[75],"As":[76],"an":[77,126,146,240],"important":[78],"application":[79],"this":[81,95,244],"analysis,":[82,222],"investigate":[84,171],"with":[86,189],"subset":[88,175],"selection.":[89],"In":[90],"problem,":[96],"via":[101,247],"Shannon":[103],"entropy":[104],"group":[106],"features":[108],"into":[109],"sufficiently":[110],"informative":[111],"redundant.":[113],"Then,":[114,169],"make":[116],"connection":[118],"proposed":[121,227],"derive":[125],"upper":[127],"bound":[128],"joint":[131],"entropy.":[132],"Based":[133],"that,":[135],"measure":[139,214,228,245],"quantify":[141],"present":[145,239],"algorithm.":[149],"test":[151],"our":[152,226],"method":[153],"various":[155,254],"real-world":[156],"synthetic":[158],"datasets":[159],"demonstrate":[161,194,250],"improvements":[162,252],"conventional":[164],"selection":[167,176,257],"techniques.":[168],"reformulate":[178],"it":[179],"domain.":[183],"Bridging":[184],"Bayesian":[186],"error":[187],"rate":[188],"coefficients,":[192],"that":[195,225],"provides":[199],"powerful":[201],"tool":[202],"dependencies.":[207],"Further,":[208],"introduce":[210],"computationally":[212],"efficient":[213],"selecting":[216],"relevant":[217],"features.":[218],"Via":[219],"theoretical":[221],"show":[224],"finds":[229],"provably":[230],"<italic":[231],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[232],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">asymptotically":[233],"optimal</i>":[234],"subsets.":[236],"Lastly,":[237],"algorithm":[241],"based":[242],"numerical":[248],"experiments":[249],"its":[251],"algorithms.":[258]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}