{"id":"https://openalex.org/W3193697567","doi":"https://doi.org/10.1109/ssp49050.2021.9513828","title":"Weighed \u2113<sub>1</sub> on the Simplex: Compressive Sensing Meets Locality","display_name":"Weighed \u2113<sub>1</sub> on the Simplex: Compressive Sensing Meets Locality","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3193697567","doi":"https://doi.org/10.1109/ssp49050.2021.9513828","mag":"3193697567"},"language":"en","primary_location":{"id":"doi:10.1109/ssp49050.2021.9513828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","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/A5061037144","display_name":"Abiy Tasissa","orcid":"https://orcid.org/0000-0003-4033-7735"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abiy Tasissa","raw_affiliation_strings":["Tufts University, Medford, MA"],"affiliations":[{"raw_affiliation_string":"Tufts University, Medford, MA","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084760979","display_name":"Pranay Tankala","orcid":"https://orcid.org/0000-0002-4424-0853"},"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":"Pranay Tankala","raw_affiliation_strings":["School of Engineering and Applied Sciences, Harvard University, Cambridge, MA"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Harvard University, Cambridge, MA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002643771","display_name":"Demba Ba","orcid":"https://orcid.org/0000-0002-1139-1030"},"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":"Demba Ba","raw_affiliation_strings":["School of Engineering and Applied Sciences, Harvard University, Cambridge, MA"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Harvard University, Cambridge, MA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061037144"],"corresponding_institution_ids":["https://openalex.org/I121934306"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12027268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"290","issue":null,"first_page":"476","last_page":"480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/manifold","display_name":"Manifold (fluid mechanics)","score":0.5792128443717957},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.519816517829895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5040473341941833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49905943870544434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3708301782608032},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.36934441328048706},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3250874876976013},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32410627603530884}],"concepts":[{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.5792128443717957},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.519816517829895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5040473341941833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49905943870544434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3708301782608032},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.36934441328048706},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3250874876976013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32410627603530884},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp49050.2021.9513828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1856231595","https://openalex.org/W1963932623","https://openalex.org/W1980079540","https://openalex.org/W1993962865","https://openalex.org/W2002827932","https://openalex.org/W2023630749","https://openalex.org/W2053186076","https://openalex.org/W2101008719","https://openalex.org/W2108119513","https://openalex.org/W2111394763","https://openalex.org/W2112796928","https://openalex.org/W2134074206","https://openalex.org/W2136235822","https://openalex.org/W2150593711","https://openalex.org/W2153663612","https://openalex.org/W2154332973","https://openalex.org/W2157872906","https://openalex.org/W2160547390","https://openalex.org/W2164452299","https://openalex.org/W2165874743","https://openalex.org/W2180180824","https://openalex.org/W2762625016","https://openalex.org/W2949942380","https://openalex.org/W2955180871","https://openalex.org/W2963326510","https://openalex.org/W2963697946","https://openalex.org/W2999795752","https://openalex.org/W3108070605","https://openalex.org/W4206742934","https://openalex.org/W4295101905","https://openalex.org/W6638914580","https://openalex.org/W6675117327","https://openalex.org/W6676321539","https://openalex.org/W6683194942","https://openalex.org/W6684578312","https://openalex.org/W6786437847"],"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/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756"],"abstract_inverted_index":{"Sparse":[0],"manifold":[1,7,62,105],"learning":[2,8,63,65],"algorithms":[3],"combine":[4],"techniques":[5],"in":[6,72],"and":[9,49,88,126,142,145,154],"sparse":[10,143],"optimization":[11,136],"to":[12,33,37],"learn":[13],"features":[14],"that":[15,95,108,138],"could":[16],"be":[17,30,47],"utilized":[18],"for":[19,102],"downstream":[20],"tasks.":[21],"The":[22],"standard":[23,74],"setting":[24],"of":[25,42,120,149],"compressive":[26],"sensing":[27],"can":[28],"not":[29,51,70],"immediately":[31],"applied":[32],"this":[34],"setup.":[35],"Due":[36],"the":[38,53,109,118,140,147],"intrinsic":[39],"geometric":[40],"structure":[41],"data,":[43],"dictionary":[44,103],"atoms":[45,100],"might":[46],"redundant":[48],"do":[50],"satisfy":[52],"restricted":[54],"isometry":[55],"property":[56],"or":[57],"coherence":[58],"condition.":[59],"In":[60],"addition,":[61],"emphasizes":[64],"local":[66],"geometry":[67],"which":[68],"is":[69,111],"reflected":[71],"a":[73],"\u2113":[75,84,90,122,128],"<inf":[76,85,91,123,129],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[77,86,92,124,130],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[78,93,125],"minimization":[79],"problem.":[80],"We":[81,133],"propose":[82],"weighted":[83,89,121,127],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</inf>":[87,131],"regularizations":[94],"encourage":[96],"representation":[97],"via":[98],"neighborhood":[99],"suited":[101],"based":[104],"learning.":[106],"Assuming":[107],"data":[110],"generated":[112],"from":[113],"Delaunay":[114],"triangulation,":[115],"we":[116],"show":[117],"equivalence":[119],".":[132],"discuss":[134],"an":[135],"program":[137],"learns":[139],"dictionaries":[141],"co-efficients":[144],"demonstrate":[146],"utility":[148],"our":[150],"regularization":[151],"on":[152],"synthetic":[153],"real":[155],"datasets.":[156]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
