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ORCIDEvan Randall Sparks
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2020 – today
- 2021
[c10]Nicholas Roberts, Samuel Guo, Cong Xu, Ameet Talwalkar, David Lander, Lvfang Tao, Linhang Cai, Shuaicheng Niu, Jianyu Heng, Hongyang Qin, Minwen Deng, Johannes Hog, Alexander Pfefferle, Sushil Ammanaghatta Shivakumar, Arjun Krishnakumar, Yubo Wang, Rhea Sukthanker, Frank Hutter, Euxhen Hasanaj, Tien-Dung Le, Mikhail Khodak, Yuriy Nevmyvaka, Kashif Rasul, Frederic Sala, Anderson Schneider, Junhong Shen, Evan Randall Sparks:
AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale. NeurIPS (Competition and Demos) 2021: 151-170- 2020
- [j2]Zhao Zhang
, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter:
Kira: Processing Astronomy Imagery Using Big Data Technology. IEEE Trans. Big Data 6(2): 369-381 (2020)
2010 – 2019
- 2019
- [i10]Liam Li, Evan Randall Sparks, Kevin G. Jamieson, Ameet Talwalkar:
Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning. CoRR abs/1903.05176 (2019) - [i9]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - 2017
- [c9]Francois Belletti, Evan Randall Sparks, Alexandre M. Bayen, Joseph Gonzalez:
Random projection design for scalable implicit smoothing of randomly observed stochastic processes. AISTATS 2017: 700-708 - [c8]Zhao Zhang, Evan Randall Sparks, Michael J. Franklin:
Diagnosing Machine Learning Pipelines with Fine-grained Lineage. HPDC 2017: 143-153 - [c7]Evan Randall Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht:
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. ICDE 2017: 535-546 - [c6]Hang Qi, Evan Randall Sparks, Ameet Talwalkar:
Paleo: A Performance Model for Deep Neural Networks. ICLR (Poster) 2017 - 2016
- [b1]Evan Randall Sparks:
End-to-End Large Scale Machine Learning with KeystoneML. University of California, Berkeley, USA, 2016 - [j1]Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan Randall Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, D. B. Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar:
MLlib: Machine Learning in Apache Spark. J. Mach. Learn. Res. 17: 34:1-34:7 (2016) - [c5]Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Aaron Staple, Matei Zaharia:
Matrix Computations and Optimization in Apache Spark. KDD 2016: 31-38 - [i8]Francois W. Belletti, Evan Randall Sparks, Michael J. Franklin, Alexandre M. Bayen, Joseph E. Gonzalez:
Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies. CoRR abs/1603.03336 (2016) - [i7]Evan Randall Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht:
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. CoRR abs/1610.09451 (2016) - 2015
- [c4]Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter:
Scientific computing meets big data technology: An astronomy use case. IEEE BigData 2015: 918-927 - [c3]Evan Randall Sparks, Ameet Talwalkar, Daniel Haas, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
Automating model search for large scale machine learning. SoCC 2015: 368-380 - [i6]Evan Randall Sparks, Ameet Talwalkar, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries. CoRR abs/1502.00068 (2015) - [i5]Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan Randall Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, D. B. Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar:
MLlib: Machine Learning in Apache Spark. CoRR abs/1505.06807 (2015) - [i4]Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter:
Scientific Computing Meets Big Data Technology: An Astronomy Use Case. CoRR abs/1507.03325 (2015) - [i3]Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Alexander Ulanov, Matei Zaharia:
linalg: Matrix Computations in Apache Spark. CoRR abs/1509.02256 (2015) - [i2]Francois Belletti, Evan Randall Sparks, Michael J. Franklin, Alexandre M. Bayen:
Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems. CoRR abs/1511.06493 (2015) - 2013
- [c2]Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
MLI: An API for Distributed Machine Learning. ICDM 2013: 1187-1192 - [i1]Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
MLI: An API for Distributed Machine Learning. CoRR abs/1310.5426 (2013)
2000 – 2009
- 2008
- [c1]Sergey Bratus, Nihal D'Cunha, Evan Randall Sparks, Sean W. Smith:
TOCTOU, Traps, and Trusted Computing. TRUST 2008: 14-32
Coauthor Index
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