Peter Bailis

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Citazioni	4067	3098
Indice H	32	30
i10-index	51	48

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Matei ZahariaStanford DAWN Lab and DatabricksEmail verificata su cs.stanford.edu
Daniel KangStanford UniversityEmail verificata su stanford.edu
Joseph HellersteinJim Gray Professor of Computer Science, UC BerkeleyEmail verificata su berkeley.edu
Ion StoicaProfessor of Computer Science, UC BerkeleyEmail verificata su cs.berkeley.edu
Firas AbuzaidStanford UniversityEmail verificata su cs.stanford.edu
Alan FeketeProfessor of Enterprise Software Systems, University of SydneyEmail verificata su sydney.edu.au
Michael FranklinLiew Family Chair of Computer Science, University of ChicagoEmail verificata su uchicago.edu
Edward R GanStanford UniversityEmail verificata su stanford.edu
Kexin RongDepartment of Computer Science, Stanford UniversityEmail verificata su cs.stanford.edu
Sahaana SuriStanford UniversityEmail verificata su stanford.edu
Deepak NarayananMicrosoft ResearchEmail verificata su microsoft.com
Cody ColemanCoactive AIEmail verificata su cs.stanford.edu
Ali GhodsiUC BerkeleyEmail verificata su cs.berkeley.edu
Christopher RéComputer Science, Stanford UniversityEmail verificata su cs.stanford.edu
Kai Sheng TaiFacebook AIEmail verificata su cs.stanford.edu
Kunle OlukotunCadence Design Systems Professor of Computer Science, Stanford UniversityEmail verificata su stanford.edu
Luigi NardiAssistant Professor in ML at Lund University; Research Scientist at StanfordEmail verificata su cs.lth.se
Tian ZhaoStanford UniversityEmail verificata su stanford.edu
Shivaram VenkataramanUniversity of Wisconsin-MadisonEmail verificata su cs.wisc.edu
Gregory ValiantAssistant Professor of Computer Science, Stanford UniversityEmail verificata su stanford.edu

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Peter Bailis

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Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale. D Kang, J Emmons, F Abuzaid, P Bailis, M Zaharia PVLDB 10 (11), 1586-1597, 2017	304*	2017
Bolt-on causal consistency P Bailis, A Ghodsi, JM Hellerstein, I Stoica SIGMOD 2013, 761-772, 2013	272	2013
Dawnbench: An end-to-end deep learning benchmark and competition C Coleman, D Narayanan, D Kang, T Zhao, J Zhang, L Nardi, P Bailis, ... Training 100 (101), 102, 2017	260	2017
Probabilistically Bounded Staleness for Practical Partial Quorums P Bailis, S Venkataraman, MJ Franklin, JM Hellerstein, I Stoica Proceedings of the VLDB Endowment (PVLDB 2012) 5 (8), 776-787, 2012	253	2012
Highly Available Transactions: Virtues and Limitations P Bailis, A Davidson, A Fekete, A Ghodsi, JM Hellerstein, I Stoica Proceedings of the VLDB Endowment 7 (3), 2013	239	2013
Eventual consistency today: Limitations, extensions, and beyond P Bailis, A Ghodsi Communications of the ACM 56 (5), 55-63, 2013	229	2013
Coordination Avoidance in Database Systems P Bailis, A Fekete, A Ghodsi, JM Hellerstein, I Stoica Proceedings of the VLDB Endowment 8 (3), 2014	219*	2014
MacroBase: Prioritizing attention in fast data P Bailis, E Gan, S Madden, D Narayanan, K Rong, S Suri Proceedings of the 2017 ACM International Conference on Management of Data …, 2017	162	2017
Mlperf training benchmark P Mattson, C Cheng, G Diamos, C Coleman, P Micikevicius, D Patterson, ... Proceedings of Machine Learning and Systems 2, 336-349, 2020	159	2020
Scalable atomic visibility with RAMP transactions P Bailis, A Fekete, JM Hellerstein, A Ghodsi, I Stoica Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014	152	2014
The Network is Reliable: An informal survey of real-world communications failures P Bailis, K Kingsbury Queue 12 (7), 20, 2014	133	2014
The missing piece in complex analytics: Low latency, scalable model management and serving with velox D Crankshaw, P Bailis, JE Gonzalez, H Li, Z Zhang, MJ Franklin, A Ghodsi, ... CIDR 2015, 2014	114	2014
The potential dangers of causal consistency and an explicit solution P Bailis, A Fekete, A Ghodsi, JM Hellerstein, I Stoica Proceedings of the Third ACM Symposium on Cloud Computing, 1-7, 2012	108	2012
Blazeit: Optimizing declarative aggregation and limit queries for neural network-based video analytics D Kang, P Bailis, M Zaharia arXiv preprint arXiv:1805.01046, 2018	84*	2018
Programming micro-aerial vehicle swarms with karma K Dantu, B Kate, J Waterman, P Bailis, M Welsh 9th Annual Conference on Embedded Networked Sensor Systems, Seattle, WA, 2011	84	2011
Feral concurrency control: An empirical investigation of modern application integrity P Bailis, A Fekete, MJ Franklin, A Ghodsi, JM Hellerstein, I Stoica Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015	82	2015
Analysis of dawnbench, a time-to-accuracy machine learning performance benchmark C Coleman, D Kang, D Narayanan, L Nardi, T Zhao, J Zhang, P Bailis, ... ACM SIGOPS Operating Systems Review 53 (1), 14-25, 2019	80	2019
Quantifying eventual consistency with PBS P Bailis, S Venkataraman, MJ Franklin, JM Hellerstein, I Stoica The VLDB Journal 23 (2), 279-302, 2014	69	2014
Dimetrodon: processor-level preventive thermal management via idle cycle injection P Bailis, VJ Reddi, S Gandhi, D Brooks, M Seltzer Design Automation Conference (DAC), 2011 48th ACM/EDAC/IEEE, 89-94, 2011	58	2011
Selection via proxy: Efficient data selection for deep learning C Coleman, C Yeh, S Mussmann, B Mirzasoleiman, P Bailis, P Liang, ... arXiv preprint arXiv:1906.11829, 2019	54	2019

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