{"id":"https://openalex.org/W4387870386","doi":"https://doi.org/10.1109/mlsp55844.2023.10285982","title":"Desketching of R-Separable Matrices From Compressive Linear Measurements","display_name":"Desketching of R-Separable Matrices From Compressive Linear Measurements","publication_year":2023,"publication_date":"2023-09-17","ids":{"openalex":"https://openalex.org/W4387870386","doi":"https://doi.org/10.1109/mlsp55844.2023.10285982"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp55844.2023.10285982","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp55844.2023.10285982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5100667383","display_name":"Neha Singh","orcid":"https://orcid.org/0000-0002-0023-606X"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Neha Singh","raw_affiliation_strings":["Indian Institute of Technology Roorkee,Dept. of Elec. & Comm. Engg,Uttarakhand,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee,Dept. of Elec. & Comm. Engg,Uttarakhand,India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011671147","display_name":"Saurabh Khanna","orcid":"https://orcid.org/0000-0003-4276-3949"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saurabh Khanna","raw_affiliation_strings":["Indian Institute of Technology Roorkee,Dept. of Elec. & Comm. Engg,Uttarakhand,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee,Dept. of Elec. & Comm. Engg,Uttarakhand,India","institution_ids":["https://openalex.org/I154851008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100667383"],"corresponding_institution_ids":["https://openalex.org/I154851008"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15487494,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"1","last_page":"6"},"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9966999888420105,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/separable-space","display_name":"Separable space","score":0.8395877480506897},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7124351859092712},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.649634599685669},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5912976264953613},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5582448840141296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4974348843097687},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4938064515590668},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45749980211257935},{"id":"https://openalex.org/keywords/convex-analysis","display_name":"Convex analysis","score":0.44484901428222656},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.43808406591415405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43756580352783203},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3979471027851105},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.33067041635513306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22041535377502441},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.21009284257888794},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.14417555928230286},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.07266905903816223}],"concepts":[{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.8395877480506897},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7124351859092712},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.649634599685669},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5912976264953613},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5582448840141296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4974348843097687},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4938064515590668},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45749980211257935},{"id":"https://openalex.org/C12108790","wikidata":"https://www.wikidata.org/wiki/Q2234833","display_name":"Convex analysis","level":4,"score":0.44484901428222656},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.43808406591415405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43756580352783203},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3979471027851105},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33067041635513306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22041535377502441},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.21009284257888794},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.14417555928230286},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.07266905903816223},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp55844.2023.10285982","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp55844.2023.10285982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","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":17,"referenced_works":["https://openalex.org/W230214904","https://openalex.org/W2097273723","https://openalex.org/W2098176827","https://openalex.org/W2105503503","https://openalex.org/W2140318696","https://openalex.org/W2164696938","https://openalex.org/W2283104426","https://openalex.org/W2950517223","https://openalex.org/W2992810923","https://openalex.org/W3099308370","https://openalex.org/W4244393449","https://openalex.org/W4292363360","https://openalex.org/W6674595457","https://openalex.org/W6675606416","https://openalex.org/W6680770193","https://openalex.org/W6695703272","https://openalex.org/W6752471172"],"related_works":["https://openalex.org/W4387870386","https://openalex.org/W2040676043","https://openalex.org/W1977643895","https://openalex.org/W3125145310","https://openalex.org/W2391091101","https://openalex.org/W2051968184","https://openalex.org/W2610781457","https://openalex.org/W4256242347","https://openalex.org/W4317914276","https://openalex.org/W2510140549"],"abstract_inverted_index":{"High-dimensional":[0],"datasets":[1,104],"manifest":[2],"as":[3,13,65,77],"r-separable":[4,36,56,117],"matrices":[5,37,57,118],"in":[6,114],"a":[7,66,78],"wide":[8],"range":[9],"of":[10,22,33,55,80,85,94,109],"applications":[11],"such":[12],"hyperspectral":[14],"imaging,":[15],"text":[16],"mining,":[17],"astronomy,":[18],"and":[19,41,52,119,127],"archetypal":[20],"analysis":[21],"scientific":[23],"imaging":[24],"data.":[25],"In":[26],"this":[27],"work,":[28],"we":[29],"consider":[30],"the":[31,49,107],"problem":[32],"reconstructing":[34],"high-dimensional":[35,116],"from":[38,62,124],"their":[39,60,121,125],"compressive":[40,63,126],"noiseless":[42,128],"linear":[43,129],"measurements.":[44,130],"We":[45,97],"propose":[46],"to":[47,58,105],"exploit":[48],"convex":[50,82,122],"geometry":[51,123],"latent":[53],"sparsity":[54],"pose":[59],"desketching":[61,115],"measurements":[64],"constrained":[67],"nonconvex":[68,72],"optimization.":[69],"The":[70],"resulting":[71],"optimization":[73],"is":[74,87],"then":[75],"solved":[76,88],"sequence":[79],"reweighted":[81],"optimizations,":[83],"each":[84],"which":[86],"individually":[89],"using":[90],"Alternating":[91],"Direction":[92],"Method":[93],"Multipliers":[95],"(ADMM).":[96],"conduct":[98],"extensive":[99],"numerical":[100],"experiments":[101],"with":[102],"synthetic":[103],"demonstrate":[106],"efficacy":[108],"our":[110],"proposed":[111],"iterative":[112],"procedure":[113],"inferring":[120]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}