乐胖代购免代理版

{"id":"https://openalex.org/W3135393239","doi":"https://doi.org/10.1145/3316781.3317885","title":"ProbLP","display_name":"ProbLP","publication_year":2019,"publication_date":"2019-05-23","ids":{"openalex":"https://openalex.org/W3135393239","doi":"https://doi.org/10.1145/3316781.3317885","mag":"3135393239"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3316781.3317885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"proceedings-article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2103.00216","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082391782","display_name":"Nimish Shah","orcid":"https://orcid.org/0000-0003-3234-0715"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"funder","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Nimish Shah","raw_affiliation_strings":["MICAS, Electrical Engineering, KU Leuven"],"affiliations":[{"raw_affiliation_string":"MICAS, Electrical Engineering, KU Leuven","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083132017","display_name":"Laura Isabel Galindez Olascoaga","orcid":"https://orcid.org/0000-0001-8601-5024"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"funder","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Laura I. Galindez Olascoaga","raw_affiliation_strings":["MICAS, Electrical Engineering, KU Leuven"],"affiliations":[{"raw_affiliation_string":"MICAS, Electrical Engineering, KU Leuven","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074451226","display_name":"Wannes Meert","orcid":"https://orcid.org/0000-0001-9560-3872"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"funder","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Wannes Meert","raw_affiliation_strings":["DTAI, Computer Science, KU Leuven"],"affiliations":[{"raw_affiliation_string":"DTAI, Computer Science, KU Leuven","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012150553","display_name":"Marian Verhelst","orcid":"https://orcid.org/0000-0003-3495-9263"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"funder","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Marian Verhelst","raw_affiliation_strings":["MICAS, Electrical Engineering, KU Leuven"],"affiliations":[{"raw_affiliation_string":"MICAS, Electrical Engineering, KU Leuven","institution_ids":["https://openalex.org/I99464096"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":10,"citation_normalized_percentile":{"value":0.877684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":85,"max":86},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9983,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9983,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9807,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9776,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation","score":0.62648886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.83763874},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7745434},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.63277316},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.62648886},{"id":"https://openalex.org/C2781172179","wikidata":"https://www.wikidata.org/wiki/Q853109","display_name":"Parallelism (grammar)","level":2,"score":0.54321116},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.53721994},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4857474},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.44690484},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.42545605},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4207453},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.36467326},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33700427},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.26108286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24584097},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3316781.3317885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.00216","pdf_url":"http://arxiv.org/pdf/2103.00216","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/638934","pdf_url":"https://lirias.kuleuven.be/bitstream/123456789/638934/2/DAC_conference_2019_ACM_OA.pdf","source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":["KU Leuven"],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"acceptedVersion","is_accepted":true,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2103.00216","pdf_url":"https://arxiv.org/pdf/2103.00216","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2103.00216","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.00216","pdf_url":"http://arxiv.org/pdf/2103.00216","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.92}],"grants":[],"datasets":[],"versions":["https://openalex.org/W2946077262","https://openalex.org/W3135393239"],"referenced_works_count":23,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W1505477995","https://openalex.org/W1551607660","https://openalex.org/W2015889257","https://openalex.org/W2020804487","https://openalex.org/W2028980143","https://openalex.org/W2034308417","https://openalex.org/W2062818807","https://openalex.org/W2134524950","https://openalex.org/W2159080219","https://openalex.org/W2162410259","https://openalex.org/W2555209581","https://openalex.org/W2765332150","https://openalex.org/W2804796373","https://openalex.org/W2810218749","https://openalex.org/W2898962957","https://openalex.org/W2910818680","https://openalex.org/W2911640577","https://openalex.org/W3020913839","https://openalex.org/W3022909171","https://openalex.org/W3098971702","https://openalex.org/W4240495026","https://openalex.org/W4298084898"],"related_works":["https://openalex.org/W4386557346","https://openalex.org/W3014500535","https://openalex.org/W3013241373","https://openalex.org/W2504075107","https://openalex.org/W2354058185","https://openalex.org/W2319812372","https://openalex.org/W2162409446","https://openalex.org/W2109463584","https://openalex.org/W2045183646","https://openalex.org/W1482096554"],"abstract_inverted_index":{"Bayesian":[0],"reasoning":[1],"is":[2,30,93],"a":[3,15,49],"powerful":[4],"mechanism":[5],"for":[6,80],"probabilistic":[7,59],"inference":[8,28,60,83],"in":[9],"smart":[10],"edge-devices.":[11],"During":[12],"such":[13],"inferences,":[14],"low-precision":[16,41,58,89],"arithmetic":[17],"representation":[18,68],"can":[19],"enable":[20],"improved":[21],"energy":[22],"efficiency.":[23],"However,":[24],"its":[25],"impact":[26],"on":[27,70,95],"accuracy":[29],"not":[31,38],"yet":[32],"understood.":[33],"Furthermore,":[34],"general-purpose":[35],"hardware":[36,74,79],"does":[37],"natively":[39],"support":[40],"representation.":[42],"To":[43],"address":[44],"this,":[45],"we":[46],"propose":[47],"ProbLP,":[48],"framework":[50,92],"that":[51],"automates":[52],"the":[53,81],"analysis":[54],"and":[55,73,88],"design":[56],"of":[57],"hardware.":[61],"It":[62,76],"automatically":[63],"chooses":[64],"an":[65],"appropriate":[66],"energy-efficient":[67],"based":[69],"worst-case":[71],"error-bounds":[72],"energy-models.":[75],"generates":[77],"custom":[78],"resulting":[82],"network":[84],"exploiting":[85],"parallelism,":[86],"pipelining":[87],"operation.":[90],"The":[91],"validated":[94],"several":[96],"embedded-sensing":[97],"benchmarks.":[98]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3135393239","counts_by_year":[{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2025-02-25T11:45:52.362002","created_date":"2021-03-15"}