{"id":"https://openalex.org/W2588688853","doi":"https://doi.org/10.1109/allerton.2016.7852248","title":"Interpretable machine learning via convex cardinal shape composition","display_name":"Interpretable machine learning via convex cardinal shape composition","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2588688853","doi":"https://doi.org/10.1109/allerton.2016.7852248","mag":"2588688853"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2016.7852248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2016.7852248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","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/A5015286159","display_name":"Kush R. Varshney","orcid":"https://orcid.org/0000-0002-7376-5536"},"institutions":[{"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":true,"raw_author_name":"Kush R. Varshney","raw_affiliation_strings":["Mathematical Sciences Department, IBM Thomas J. Watson Research Center Yorktown Heights, New York"],"affiliations":[{"raw_affiliation_string":"Mathematical Sciences Department, IBM Thomas J. Watson Research Center Yorktown Heights, New York","institution_ids":["https://openalex.org/I4210114115"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5015286159"],"corresponding_institution_ids":["https://openalex.org/I4210114115"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6901841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"327","last_page":"330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.989300012588501,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.989300012588501,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9835000038146973,"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":0.9789000153541565,"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/interpretability","display_name":"Interpretability","score":0.9256208539009094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6750912070274353},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6120370626449585},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5850087404251099},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5630126595497131},{"id":"https://openalex.org/keywords/composition","display_name":"Composition (language)","score":0.5151358842849731},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49088388681411743},{"id":"https://openalex.org/keywords/hinge-loss","display_name":"Hinge loss","score":0.4858510196208954},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4353324770927429},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.41894227266311646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38474011421203613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2507266104221344},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.18622902035713196}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9256208539009094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6750912070274353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6120370626449585},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5850087404251099},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5630126595497131},{"id":"https://openalex.org/C40231798","wikidata":"https://www.wikidata.org/wiki/Q1333743","display_name":"Composition (language)","level":2,"score":0.5151358842849731},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49088388681411743},{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.4858510196208954},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4353324770927429},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.41894227266311646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38474011421203613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2507266104221344},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.18622902035713196},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/allerton.2016.7852248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2016.7852248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W134253518","https://openalex.org/W1523554224","https://openalex.org/W1567012231","https://openalex.org/W1670263352","https://openalex.org/W1700397478","https://openalex.org/W2025223104","https://openalex.org/W2025587182","https://openalex.org/W2026905436","https://openalex.org/W2063813235","https://openalex.org/W2097472698","https://openalex.org/W2115899769","https://openalex.org/W2116040950","https://openalex.org/W2118022153","https://openalex.org/W2128420091","https://openalex.org/W2130698119","https://openalex.org/W2148395215","https://openalex.org/W2164878629","https://openalex.org/W2170708028","https://openalex.org/W2233387570","https://openalex.org/W2236721743","https://openalex.org/W2249156281","https://openalex.org/W2282127401","https://openalex.org/W2289204371","https://openalex.org/W2428981601","https://openalex.org/W2467594271","https://openalex.org/W2555206781","https://openalex.org/W2963040191","https://openalex.org/W2963604310","https://openalex.org/W2964112969","https://openalex.org/W2964134873","https://openalex.org/W3005392388","https://openalex.org/W3121410165","https://openalex.org/W3124792046","https://openalex.org/W4212971335","https://openalex.org/W4243528505","https://openalex.org/W6605501381","https://openalex.org/W6633346352","https://openalex.org/W6633888031","https://openalex.org/W6634150524","https://openalex.org/W6637586372","https://openalex.org/W6684997022","https://openalex.org/W6695065555","https://openalex.org/W6696322540","https://openalex.org/W6730095454"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"For":[0],"safety":[1],"reasons,":[2],"the":[3,38,84],"interpretability":[4],"of":[5,12,80],"models":[6,75],"is":[7],"important":[8],"in":[9,15,37,56,83],"consequential":[10],"applications":[11],"supervised":[13],"classification":[14],"which":[16],"predictions":[17],"are":[18],"used":[19,86],"to":[20,48,87],"support":[21],"human":[22],"decision":[23,89],"makers.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"extend":[29],"cardinal":[30],"shape":[31,69],"composition,":[32],"a":[33,57,68],"new":[34],"method":[35],"developed":[36],"image":[39,46],"processing":[40],"and":[41],"computer":[42],"vision":[43],"literature":[44],"for":[45],"segmentation,":[47],"general":[49],"machine":[50],"learning":[51],"problems.":[52],"Our":[53],"transformation":[54],"results":[55],"computationally-tractable":[58],"\u2113":[59],"<sub":[60],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[61],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[62],"-regularized":[63],"hinge":[64],"loss":[65],"optimization":[66],"over":[67],"dictionary.":[70],"This":[71],"approach":[72],"yields":[73],"human-interpretable":[74],"with":[76],"an":[77],"appropriate":[78],"choice":[79],"atomic":[81],"shapes":[82],"dictionary":[85],"compose":[88],"boundaries.":[90]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}