{"id":"https://openalex.org/W2169074448","doi":"https://doi.org/10.1109/icassp.2008.4518453","title":"A new approach to constrained expectation-maximization for density estimation","display_name":"A new approach to constrained expectation-maximization for density estimation","publication_year":2008,"publication_date":"2008-03-01","ids":{"openalex":"https://openalex.org/W2169074448","doi":"https://doi.org/10.1109/icassp.2008.4518453","mag":"2169074448"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2008.4518453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4518453","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5064278274","display_name":"Hunsop Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hunsop Hong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Hunsop Hong and Dan Schonfeld, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Hunsop Hong and Dan Schonfeld, Chicago, IL, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081723612","display_name":"Dan Schonfeld","orcid":"https://orcid.org/0000-0002-2772-4821"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Schonfeld","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Hunsop Hong and Dan Schonfeld, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Hunsop Hong and Dan Schonfeld, Chicago, IL, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064278274"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3539,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.58220339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3689","last_page":"3692"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9959999918937683,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9959999918937683,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9937000274658203,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/entropy-maximization","display_name":"Entropy maximization","score":0.7702113389968872},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.7676244974136353},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7205122709274292},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6708132028579712},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.5957040786743164},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5742042660713196},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5553714036941528},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.49920153617858887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.453371524810791},{"id":"https://openalex.org/keywords/penalty-method","display_name":"Penalty method","score":0.4480467736721039},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4232065975666046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41829565167427063},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.3831106126308441},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38281968235969543},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.24853259325027466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1991252899169922},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13430938124656677},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.09763714671134949}],"concepts":[{"id":"https://openalex.org/C127233936","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Entropy maximization","level":3,"score":0.7702113389968872},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.7676244974136353},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7205122709274292},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6708132028579712},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.5957040786743164},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5742042660713196},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5553714036941528},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.49920153617858887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.453371524810791},{"id":"https://openalex.org/C6180225","wikidata":"https://www.wikidata.org/wiki/Q3411771","display_name":"Penalty method","level":2,"score":0.4480467736721039},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4232065975666046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41829565167427063},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3831106126308441},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38281968235969543},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.24853259325027466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1991252899169922},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13430938124656677},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.09763714671134949},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2008.4518453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4518453","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","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":9,"referenced_works":["https://openalex.org/W2049633694","https://openalex.org/W2066882228","https://openalex.org/W2067191022","https://openalex.org/W2116801843","https://openalex.org/W2118020555","https://openalex.org/W2567948266","https://openalex.org/W3129711340","https://openalex.org/W4251171122","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W1636292289","https://openalex.org/W2951493954","https://openalex.org/W2169074448","https://openalex.org/W1971754175","https://openalex.org/W2251843845","https://openalex.org/W2073182819","https://openalex.org/W2165173554","https://openalex.org/W2084311655","https://openalex.org/W1534559501","https://openalex.org/W2147030611"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"two":[5],"density":[6,30,41,55],"estimation":[7,42,78],"methods":[8],"based":[9],"on":[10],"constrained":[11,69],"expectation-maximization":[12,20,37,70],"(EM)":[13],"algorithm.":[14],"We":[15,32],"propose":[16,34],"a":[17,25],"penalty-based":[18],"maximum-entropy":[19],"(MEEM)":[21],"algorithm":[22,39],"to":[23,45,62],"obtain":[24],"smooth":[26],"estimate":[27],"of":[28,52,66],"the":[29,53,64,67],"function.":[31,56],"further":[33],"an":[35],"attraction-repulsion":[36],"(AREM)":[38],"for":[40],"in":[43,72],"order":[44],"determine":[46],"equilibrium":[47],"between":[48],"over-smoothing":[49],"and":[50,75],"over-fitting":[51],"estimated":[54],"Computer":[57],"simulation":[58],"results":[59],"are":[60],"used":[61],"show":[63],"effectiveness":[65],"proposed":[68],"algorithms":[71],"image":[73],"reconstruction":[74],"sensor":[76],"field":[77],"from":[79],"randomly":[80],"scattered":[81],"samples.":[82]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
