Seuraa
Tim Kraska
Tim Kraska
MIT
Vahvistettu sähköpostiosoite verkkotunnuksessa mit.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
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
8482018
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
8452011
Crowder: Crowdsourcing entity resolution
J Wang, T Kraska, MJ Franklin, J Feng
arXiv preprint arXiv:1208.1927, 2012
7002012
MLbase: A Distributed Machine-learning System.
T Kraska, A Talwalkar, JC Duchi, R Griffith, MJ Franklin, MI Jordan
Cidr 1, 2-1, 2013
4542013
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
4242008
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
3902010
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
3542009
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
3152013
Neo: A learned query optimizer
R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ...
arXiv preprint arXiv:1904.03711, 2019
2812019
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
2582009
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
2552013
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
2392013
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
2142018
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
2002020
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
1872015
Automating model search for large scale machine learning
ER Sparks, A Talwalkar, D Haas, MJ Franklin, MI Jordan, T Kraska
Proceedings of the Sixth ACM Symposium on Cloud Computing, 368-380, 2015
178*2015
Sagedb: A learned database system
T Kraska, M Alizadeh, A Beutel, EH Chi, J Ding, A Kristo, G Leclerc, ...
1772021
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
165*2019
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
1632019
A sample-and-clean framework for fast and accurate query processing on dirty data
J Wang, S Krishnan, MJ Franklin, K Goldberg, T Kraska, T Milo
Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014
1622014
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Artikkelit 1–20