乐胖代购免代理版

{"id":"https://openalex.org/W2757079466","doi":"https://doi.org/10.18653/v1/d17-1046","title":"Why ADAGRAD Fails for Online Topic Modeling","display_name":"Why ADAGRAD Fails for Online Topic Modeling","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2757079466","doi":"https://doi.org/10.18653/v1/d17-1046","mag":"2757079466"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1046","pdf_url":"https://www.aclweb.org/anthology/D17-1046.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.aclweb.org/anthology/D17-1046.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032483127","display_name":"You L\u00fc","orcid":"https://orcid.org/0000-0002-4357-1888"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"You Lu","raw_affiliation_strings":["Computer Science (CS) University of Colorado Boulder Boulder, CO"],"affiliations":[{"raw_affiliation_string":"Computer Science (CS) University of Colorado Boulder Boulder, CO","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082626147","display_name":"Jeffrey Lund","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey Lund","raw_affiliation_strings":["Computer Science (CS) Brigham Young University Provo, UT"],"affiliations":[{"raw_affiliation_string":"Computer Science (CS) Brigham Young University Provo, UT","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081307846","display_name":"Jordan Boyd\u2010Graber","orcid":"https://orcid.org/0000-0002-7770-4431"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jordan Boyd-Graber","raw_affiliation_strings":["iSchool, LSC, and UMIACS University of Maryland College Park, MD"],"affiliations":[{"raw_affiliation_string":"iSchool, LSC, and UMIACS University of Maryland College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.374,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.435396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":79,"max":81},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9949,"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":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.72340906},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.71330917},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.4897292},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.48481932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42306668},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40379596},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35898507},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.34655622},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21334803},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.079939604}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1046","pdf_url":"https://www.aclweb.org/anthology/D17-1046.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1046","pdf_url":"https://www.aclweb.org/anthology/D17-1046.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1880262756","https://openalex.org/W2005564522","https://openalex.org/W2096199223","https://openalex.org/W2108456278","https://openalex.org/W2123549998","https://openalex.org/W2146502635","https://openalex.org/W2148721460","https://openalex.org/W2158899491","https://openalex.org/W2161050705","https://openalex.org/W2164301055","https://openalex.org/W2165599843","https://openalex.org/W2166851633","https://openalex.org/W2168231600","https://openalex.org/W2174706414","https://openalex.org/W2187741934","https://openalex.org/W2252217186","https://openalex.org/W2513324517","https://openalex.org/W2952230511","https://openalex.org/W2964121744","https://openalex.org/W3012264151","https://openalex.org/W3017285694","https://openalex.org/W3101380508","https://openalex.org/W3214273223","https://openalex.org/W4252381709","https://openalex.org/W4294562888","https://openalex.org/W6908809"],"related_works":["https://openalex.org/W4321636575","https://openalex.org/W3200230513","https://openalex.org/W2962686197","https://openalex.org/W2769501189","https://openalex.org/W2741131631","https://openalex.org/W2357796999","https://openalex.org/W2226452791","https://openalex.org/W2132052677","https://openalex.org/W2055243143","https://openalex.org/W2045526782"],"abstract_inverted_index":{"Online":[0],"topic":[1,4,62],"modeling,":[2,63],"i.e.,":[3],"modeling":[5],"with":[6],"stochastic":[7],"variational":[8],"inference,":[9],"is":[10,22,47,68],"a":[11,23],"powerful":[12],"and":[13,20],"efficient":[14],"technique":[15,25],"for":[16,26],"analyzing":[17],"large":[18],"datasets,":[19],"ADAGRAD":[21,49],"widely-used":[24],"tuning":[27],"learning":[28,57,73],"rates":[29,74],"during":[30],"online":[31,61],"gradient":[32],"optimization.":[33],"However,":[34],"these":[35],"two":[36],"techniques":[37],"do":[38],"not":[39],"work":[40],"well":[41],"together.":[42],"We":[43],"show":[44],"that":[45],"this":[46],"because":[48],"uses":[50],"accumulation":[51],"of":[52,66],"previous":[53],"gradients":[54,67],"as":[55],"the":[56,64,80,86],"rates'":[58],"denominators.":[59],"For":[60],"magnitude":[65],"very":[69,77],"large.":[70],"It":[71],"causes":[72],"to":[75],"shrink":[76],"quickly,":[78],"so":[79],"parameters":[81],"cannot":[82],"fully":[83],"converge":[84],"until":[85],"training":[87],"ends":[88]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2757079466","counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-01-23T04:06:19.976901","created_date":"2017-10-06"}