Evan R. Sparks
Cited by
Cited by
Mllib: Machine learning in apache spark
X Meng, J Bradley, B Yavuz, E Sparks, S Venkataraman, D Liu, ...
The journal of machine learning research 17 (1), 1235-1241, 2016
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
Paleo: A performance model for deep neural networks
H Qi, ER Sparks, A Talwalkar
International Conference on Learning Representations, 2016
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
Keystoneml: Optimizing pipelines for large-scale advanced analytics
ER Sparks, S Venkataraman, T Kaftan, MJ Franklin, B Recht
2017 IEEE 33rd international conference on data engineering (ICDE), 535-546, 2017
Matrix computations and optimization in apache spark
R Bosagh Zadeh, X Meng, A Ulanov, B Yavuz, L Pu, S Venkataraman, ...
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016
TOCTOU, traps, and trusted computing
S Bratus, N D’Cunha, E Sparks, SW Smith
International Conference on Trusted Computing, 14-32, 2008
A Security Assessment of Trusted Platform Modules
ER Sparks
Technical report, Department of Computer Science, 2007
Scientific computing meets big data technology: An astronomy use case
Z Zhang, K Barbary, FA Nothaft, E Sparks, O Zahn, MJ Franklin, ...
2015 IEEE International Conference on Big Data (Big Data), 918-927, 2015
Kira: Processing astronomy imagery using big data technology
Z Zhang, K Barbary, FA Nothaft, ER Sparks, O Zahn, MJ Franklin, ...
IEEE Transactions on Big Data 6 (2), 369-381, 2016
Sysml: The new frontier of machine learning systems
A Ratner, D Alistarh, G Alonso, P Bailis, S Bird, N Carlini, B Catanzaro, ...
arXiv preprint arXiv:1904.03257, 2019
Diagnosing machine learning pipelines with fine-grained lineage
Z Zhang, ER Sparks, MJ Franklin
Proceedings of the 26th international symposium on high-performance parallel …, 2017
Tupaq: An efficient planner for large-scale predictive analytic queries
ER Sparks, A Talwalkar, MJ Franklin, MI Jordan, T Kraska
arXiv preprint arXiv:1502.00068, 2015
Search activity prediction
C Ahlberg, B Ladd, E Sparks
US Patent 11,755,663, 2023
Mlbase: A distributed machine learning wrapper
A Talwalkar, T Kraska, R Griffith, J Duchi, J Gonzalez, D Britz, X Pan, ...
NIPS Big Learning Workshop, 35, 2012
Mlsys: The new frontier of machine learning systems
A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ...
arXiv preprint arXiv:1904.03257, 2019
ML pipelines: a new high-level API for MLlib
X Meng, J Bradley, E Sparks, S Venkataraman
Nine Young Bankers Who Changed America: Thomas Sudman
E Sparks
ABA Banking Journal, 2017
A security assessment of trusted platform modules computer science technical report TR2007-597
ER Sparks, ER Sparks
Dept. Comput. Sci., Dartmouth College, Hanover, NH, USA, Tech. Rep., TR2007-597, 2007
MLlib &
E Sparks
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