Evan R. Sparks

Publication Activity (10 Years)

Years Active: 2008-2021
Publications (10 Years): 12

Top Topics

Machine Learning

Business Analytics

Top Venues

Publications

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 R. Sparks
AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale. NeurIPS (Competition and Demos) (2021)
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan R. 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) (2020)
Liam Li, Evan R. Sparks, Kevin G. Jamieson, Ameet Talwalkar
Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning. CoRR (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric 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 R. 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 (2019)
Hang Qi, Evan R. Sparks, Ameet Talwalkar
Paleo: A Performance Model for Deep Neural Networks. ICLR (Poster) (2017)
Evan R. Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. ICDE (2017)
Zhao Zhang, Evan R. Sparks, Michael J. Franklin
Diagnosing Machine Learning Pipelines with Fine-grained Lineage. HPDC (2017)
Francois Belletti, Evan R. Sparks, Alexandre M. Bayen, Joseph Gonzalez
Random projection design for scalable implicit smoothing of randomly observed stochastic processes. AISTATS (2017)
Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan R. 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 (2016)
Francois W. Belletti, Evan R. Sparks, Michael J. Franklin, Alexandre M. Bayen, Joseph E. Gonzalez
Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies. CoRR (2016)
Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan R. Sparks, Aaron Staple, Matei Zaharia
Matrix Computations and Optimization in Apache Spark. KDD (2016)
Evan R. Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. CoRR (2016)
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan R. Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
Scientific computing meets big data technology: An astronomy use case. IEEE BigData (2015)
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan R. Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
Scientific Computing Meets Big Data Technology: An Astronomy Use Case. CoRR (2015)
Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan R. 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 (2015)
Evan R. Sparks, Ameet Talwalkar, Daniel Haas, Michael J. Franklin, Michael I. Jordan, Tim Kraska
Automating model search for large scale machine learning. SoCC (2015)
Francois Belletti, Evan R. Sparks, Michael J. Franklin, Alexandre M. Bayen
Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems. CoRR (2015)
Evan R. Sparks, Ameet Talwalkar, Michael J. Franklin, Michael I. Jordan, Tim Kraska
TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries. CoRR (2015)
Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan R. Sparks, Alexander Ulanov, Matei Zaharia
linalg: Matrix Computations in Apache Spark. CoRR (2015)
Evan R. 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)
Evan R. 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 (2013)
Sergey Bratus, Nihal D'Cunha, Evan R. Sparks, Sean W. Smith
TOCTOU, Traps, and Trusted Computing. TRUST (2008)