Tim Kraska

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Michael FranklinUniversity of ChicagoDirección de correo verificada de uchicago.edu
Carsten BinnigFull Professor, Computer Science, TU DarmstadtDirección de correo verificada de tu-darmstadt.de
Samuel MaddenMITDirección de correo verificada de csail.mit.edu
Jiannan WangAssociate Professor, Simon Fraser UniversityDirección de correo verificada de sfu.ca
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Stanley ZdonikBrown UniversityDirección de correo verificada de cs.brown.edu
Ameet TalwalkarCMUDirección de correo verificada de cmu.edu
Sanjay KrishnanUniversity of ChicagoDirección de correo verificada de cs.uchicago.edu
Reynold XinDatabricksDirección de correo verificada de databricks.com
Jianhua FengProfessor of Computer Science, Tsinghua University Dirección de correo verificada de mail.tsinghua.edu.cn
Matthias BrantnerResearcher at Oracle LabsDirección de correo verificada de oracle.com
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityDirección de correo verificada de stanford.edu
Peter M. FischerProfessor for Databases and Information Systems, CS Department, University of Augsburg, GermanyDirección de correo verificada de informatik.uni-augsburg.de
Alan FeketeProfessor of Enterprise Software Systems, University of SydneyDirección de correo verificada de sydney.edu.au
David PattersonProfessor of Computer Science, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Evan R. SparksHPE, Determined AI

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Tim Kraska

MIT

Dirección de correo verificada de mit.edu - Página principal

Systems for ML ML for Systems


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
The case for learned index structures T Kraska, A Beutel, EH Chi, J Dean, N Polyzotis Proceedings of the 2018 international conference on management of data, 489-504, 2018	1197	2018
CrowdDB: answering queries with crowdsourcing MJ Franklin, D Kossmann, T Kraska, S Ramesh, R Xin Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011	882	2011
Crowder: Crowdsourcing entity resolution J Wang, T Kraska, MJ Franklin, J Feng arXiv preprint arXiv:1208.1927, 2012	752	2012
MLbase: A Distributed Machine-learning System. T Kraska, A Talwalkar, JC Duchi, R Griffith, MJ Franklin, MI Jordan Cidr 1, 2-1, 2013	483	2013
Neo: A learned query optimizer R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ... arXiv preprint arXiv:1904.03711, 2019	450	2019
Building a database on S3 M Brantner, D Florescu, D Graf, D Kossmann, T Kraska Proceedings of the 2008 ACM SIGMOD international conference on Management of …, 2008	445	2008
An evaluation of alternative architectures for transaction processing in the cloud D Kossmann, T Kraska, S Loesing Proceedings of the 2010 ACM SIGMOD International Conference on Management of …, 2010	402	2010
Consistency rationing in the cloud: Pay only when it matters T Kraska, M Hentschel, G Alonso, D Kossmann Proceedings of the VLDB Endowment 2 (1), 253-264, 2009	375	2009
MDCC: Multi-data center consistency T Kraska, G Pang, MJ Franklin, S Madden, A Fekete Proceedings of the 8th ACM European Conference on Computer Systems, 113-126, 2013	353	2013
ALEX: an updatable adaptive learned index J Ding, UF Minhas, J Yu, C Wang, J Do, Y Li, H Zhang, B Chandramouli, ... Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020	331	2020
Superneurons: Dynamic GPU memory management for training deep neural networks L Wang, J Ye, Y Zhao, W Wu, A Li, SL Song, Z Xu, T Kraska Proceedings of the 23rd ACM SIGPLAN symposium on principles and practice of …, 2018	305	2018
Leveraging transitive relations for crowdsourced joins J Wang, G Li, T Kraska, MJ Franklin, J Feng Proceedings of the 2013 ACM SIGMOD International Conference on Management of …, 2013	268	2013
Sherlock: A deep learning approach to semantic data type detection M Hulsebos, K Hu, M Bakker, E Zgraggen, A Satyanarayan, T Kraska, ... Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019	267	2019
How is the weather tomorrow? Towards a benchmark for the cloud C Binnig, D Kossmann, T Kraska, S Loesing Proceedings of the Second International Workshop on Testing Database Systems …, 2009	267	2009
Vizml: A machine learning approach to visualization recommendation K Hu, MA Bakker, S Li, T Kraska, C Hidalgo Proceedings of the 2019 CHI conference on human factors in computing systems …, 2019	264	2019
MLI: An API for distributed machine learning ER Sparks, A Talwalkar, V Smith, J Kottalam, X Pan, J Gonzalez, ... 2013 IEEE 13th International Conference on Data Mining, 1187-1192, 2013	246	2013
Fiting-tree: A data-aware index structure A Galakatos, M Markovitch, C Binnig, R Fonseca, T Kraska Proceedings of the 2019 international conference on management of data, 1189 …, 2019	245*	2019
Learning multi-dimensional indexes V Nathan, J Ding, M Alizadeh, T Kraska Proceedings of the 2020 ACM SIGMOD international conference on management of …, 2020	240	2020
Bao: Making learned query optimization practical R Marcus, P Negi, H Mao, N Tatbul, M Alizadeh, T Kraska Proceedings of the 2021 International Conference on Management of Data, 1275 …, 2021	228	2021
The end of slow networks: It's time for a redesign C Binnig, A Crotty, A Galakatos, T Kraska, E Zamanian arXiv preprint arXiv:1504.01048, 2015	222	2015

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