{"id":"https://openalex.org/W3203641084","doi":"https://doi.org/10.1109/iros47612.2022.9982105","title":"Classification of Time-Series Data Using Boosted Decision Trees","display_name":"Classification of Time-Series Data Using Boosted Decision Trees","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W3203641084","doi":"https://doi.org/10.1109/iros47612.2022.9982105","mag":"3203641084"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9982105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9982105","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5042146883","display_name":"Erfan Aasi","orcid":null},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erfan Aasi","raw_affiliation_strings":["Boston University,Boston,MA,USA,02215"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University,Boston,MA,USA,02215","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086654963","display_name":"Cristian-Ioan Vasile","orcid":"https://orcid.org/0000-0002-1132-1462"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cristian Ioan Vasile","raw_affiliation_strings":["Lehigh University,Bethlehem,PA,USA,18015"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lehigh University,Bethlehem,PA,USA,18015","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058074218","display_name":"Mahroo Bahreinian","orcid":"https://orcid.org/0000-0002-2103-597X"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahroo Bahreinian","raw_affiliation_strings":["Boston University,Boston,MA,USA,02215"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University,Boston,MA,USA,02215","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086742095","display_name":"C\u0103lin Belta","orcid":"https://orcid.org/0000-0002-7141-2657"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Calin Belta","raw_affiliation_strings":["Boston University,Boston,MA,USA,02215"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University,Boston,MA,USA,02215","institution_ids":["https://openalex.org/I111088046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8459,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.87266227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1263","last_page":"1268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9878000020980835,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9778000116348267,"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":0.9644965529441833},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.7963451147079468},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7216839790344238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6495599746704102},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6081316471099854},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5343733429908752},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5092614889144897},{"id":"https://openalex.org/keywords/binary-decision-diagram","display_name":"Binary decision diagram","score":0.48439890146255493},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45271337032318115},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.43920114636421204},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4244692921638489},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18214762210845947}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9644965529441833},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7963451147079468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7216839790344238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495599746704102},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6081316471099854},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5343733429908752},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5092614889144897},{"id":"https://openalex.org/C3309909","wikidata":"https://www.wikidata.org/wiki/Q864155","display_name":"Binary decision diagram","level":2,"score":0.48439890146255493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45271337032318115},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.43920114636421204},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4244692921638489},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18214762210845947},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9982105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9982105","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G4553413310","display_name":"NRI: FND: A Formal Methods Approach to Safe, Composable, and Distributed Reinforcement Learning for co-Robots","funder_award_id":"2024606","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W1533557569","https://openalex.org/W1547304883","https://openalex.org/W1796872423","https://openalex.org/W1988790447","https://openalex.org/W2112716550","https://openalex.org/W2117189826","https://openalex.org/W2117812871","https://openalex.org/W2148239836","https://openalex.org/W2152195021","https://openalex.org/W2312067050","https://openalex.org/W2330820318","https://openalex.org/W2339807279","https://openalex.org/W2474788619","https://openalex.org/W2543580944","https://openalex.org/W2616554232","https://openalex.org/W2795506272","https://openalex.org/W2807161818","https://openalex.org/W2912432686","https://openalex.org/W2956034981","https://openalex.org/W2962867954","https://openalex.org/W2972698871","https://openalex.org/W2972892807","https://openalex.org/W3021068062","https://openalex.org/W3092068599","https://openalex.org/W3100743289","https://openalex.org/W3140654866","https://openalex.org/W3141989474","https://openalex.org/W3154466073","https://openalex.org/W4236362309","https://openalex.org/W4295719664","https://openalex.org/W6745935785","https://openalex.org/W6793246665"],"related_works":["https://openalex.org/W4293151273","https://openalex.org/W3202881146","https://openalex.org/W4205206396","https://openalex.org/W2965693718","https://openalex.org/W1618196697","https://openalex.org/W4210628983","https://openalex.org/W2368866852","https://openalex.org/W2623725391","https://openalex.org/W2385238472","https://openalex.org/W2756012949"],"abstract_inverted_index":{"Time-series":[0],"data":[1],"classification":[2,97,124],"is":[3,102,107],"central":[4],"to":[5,71,94,114],"the":[6,96],"analysis":[7],"and":[8,16,49,118,123,134],"control":[9],"of":[10,29,89,112,126],"autonomous":[11,43],"systems,":[12],"such":[13,30,41],"as":[14,27,42,78],"robots":[15],"self-driving":[17],"cars.":[18],"Temporal":[19,80],"logic-based":[20],"learning":[21,63],"algorithms":[22],"have":[23],"been":[24],"proposed":[25],"recently":[26],"classifiers":[28,74],"data.":[31],"However,":[32],"current":[33],"frameworks":[34],"are":[35,76,129],"either":[36],"inaccurate":[37],"for":[38],"real-world":[39],"applications,":[40],"driving,":[44],"or":[45],"they":[46],"generate":[47,72,115],"long":[48],"complicated":[50],"formulae":[51,117],"that":[52,75,106],"lack":[53],"interpretability.":[54,120],"To":[55],"address":[56],"these":[57],"limitations,":[58],"we":[59],"introduce":[60],"a":[61,103,110],"novel":[62],"method,":[64],"called":[65],"Boosted":[66],"Concise":[67,90],"Decision":[68,91],"Trees":[69,92],"(BCDTs),":[70],"binary":[73],"represented":[77],"Signal":[79],"Logic":[81],"(STL)":[82],"formulae.":[83],"Our":[84],"algorithm":[85,128],"leverages":[86],"an":[87],"ensemble":[88],"(CDTs)":[93],"improve":[95,119],"performance,":[98],"where":[99],"each":[100],"CDT":[101],"decision":[104],"tree":[105],"empowered":[108],"by":[109],"set":[111],"techniques":[113],"simpler":[116],"The":[121],"effectiveness":[122],"performance":[125],"our":[127],"evaluated":[130],"on":[131],"naval":[132],"surveillance":[133],"urban-driving":[135],"case":[136],"studies.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}