{"id":"https://openalex.org/W3184669447","doi":"https://doi.org/10.23919/acc50511.2021.9482721","title":"Discounted online Newton method for time-varying time series prediction","display_name":"Discounted online Newton method for time-varying time series prediction","publication_year":2021,"publication_date":"2021-05-25","ids":{"openalex":"https://openalex.org/W3184669447","doi":"https://doi.org/10.23919/acc50511.2021.9482721","mag":"3184669447"},"language":"en","primary_location":{"id":"doi:10.23919/acc50511.2021.9482721","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc50511.2021.9482721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 American Control Conference (ACC)","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/A5008672638","display_name":"Dong-Sheng Ding","orcid":"https://orcid.org/0000-0002-5051-4777"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dongsheng Ding","raw_affiliation_strings":["Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024915129","display_name":"Jianjun Yuan","orcid":"https://orcid.org/0000-0003-1400-8866"},"institutions":[{"id":"https://openalex.org/I4210106647","display_name":"Expedia Group (United States)","ror":"https://ror.org/01sh85g09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210106647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianjun Yuan","raw_affiliation_strings":["Expedia Group"],"affiliations":[{"raw_affiliation_string":"Expedia Group","institution_ids":["https://openalex.org/I4210106647"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087790067","display_name":"Mihailo R. Jovanovi\u0107","orcid":"https://orcid.org/0000-0002-4181-2924"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mihailo R. Jovanovic","raw_affiliation_strings":["Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008672638"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.3486,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62308149,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1547","last_page":"1552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9965999722480774,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9886999726295471,"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/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8602725267410278},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.7085478901863098},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6760250926017761},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6608699560165405},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6447117328643799},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5687007308006287},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.5675143599510193},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.49365338683128357},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4490608870983124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.332447350025177},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29747313261032104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19676333665847778},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.1270882785320282}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8602725267410278},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.7085478901863098},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6760250926017761},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6608699560165405},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6447117328643799},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5687007308006287},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.5675143599510193},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.49365338683128357},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4490608870983124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.332447350025177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29747313261032104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19676333665847778},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.1270882785320282},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc50511.2021.9482721","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc50511.2021.9482721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6378152700","display_name":null,"funder_award_id":"ECCS-1708906,ECCS-1809833","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":31,"referenced_works":["https://openalex.org/W1969852690","https://openalex.org/W1971846819","https://openalex.org/W1992534575","https://openalex.org/W2015906000","https://openalex.org/W2126007324","https://openalex.org/W2513180554","https://openalex.org/W2531361673","https://openalex.org/W2783120670","https://openalex.org/W2798056406","https://openalex.org/W2890624904","https://openalex.org/W2916243177","https://openalex.org/W2951369818","https://openalex.org/W2963903516","https://openalex.org/W2998089837","https://openalex.org/W3020044295","https://openalex.org/W3020878652","https://openalex.org/W3022458846","https://openalex.org/W3033504345","https://openalex.org/W3036864192","https://openalex.org/W3040134252","https://openalex.org/W3043618167","https://openalex.org/W3045889130","https://openalex.org/W3046978353","https://openalex.org/W3107101066","https://openalex.org/W3122455386","https://openalex.org/W3125740183","https://openalex.org/W4205841652","https://openalex.org/W6678894327","https://openalex.org/W6728396080","https://openalex.org/W6754148645","https://openalex.org/W6769324986"],"related_works":["https://openalex.org/W3175321409","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W4391216528","https://openalex.org/W4312309719","https://openalex.org/W2980748541","https://openalex.org/W4399581288","https://openalex.org/W4313123484","https://openalex.org/W3041944716"],"abstract_inverted_index":{"We":[0,15],"develop":[1],"an":[2],"online":[3,33,99],"convex":[4],"optimization":[5],"method":[6,35],"for":[7,36],"predicting":[8],"time":[9,40],"series":[10],"based":[11,73],"on":[12,70,74],"streaming":[13],"observations.":[14],"first":[16,91],"approximate":[17],"the":[18,52,60,83,90],"evolution":[19],"of":[20,55,64,85],"time-varying":[21,38],"autoregressive":[22],"integrated":[23],"moving":[24],"average":[25],"(ARIMA)":[26],"processes":[27],"and":[28,62,78],"then":[29],"propose":[30],"a":[31,94],"discounted":[32],"Newton":[34],"estimating":[37],"ARIMA":[39],"series.":[41],"Under":[42],"practical":[43],"assumptions,":[44],"we":[45,67,88],"establish":[46],"dynamic":[47],"regret":[48],"bounds":[49],"that":[50,97],"quantify":[51],"tracking":[53],"performance":[54],"our":[56,65,86],"algorithm.":[57],"To":[58,82],"verify":[59],"effectiveness":[61],"robustness":[63],"method,":[66],"conduct":[68],"experiments":[69],"prediction":[71,96],"problems":[72],"both":[75],"artificial":[76],"data":[77],"real-world":[79],"COVID-19":[80,95],"data.":[81],"best":[84],"knowledge,":[87],"are":[89],"to":[92],"report":[93],"utilizes":[98],"learning.":[100]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}