Evan Randall Sparks

23 papers A* 3A 2Journal 12Unranked 5

Year	Rank	Type	Title / Venue / Authors
2021	—	`conf`	AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale. NeurIPS (Competition and Demos) 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 Sanjay Sukthanker, Frank Hutter, Euxhen Hasanaj, Tien-Dung Le, Mikhail Khodak, Yuriy Nevmyvaka, Kashif Rasul, Frederic Sala, Anderson Schneider, Junhong Shen, Evan Randall Sparks
2020	J	`jnl`	Kira: Processing Astronomy Imagery Using Big Data Technology. IEEE Trans. Big Data Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
2019	J	`jnl`	Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning. CoRR Liam Li, Evan Randall Sparks, Kevin Jamieson, Ameet Talwalkar
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR 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 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
2017	A	`conf`	Diagnosing Machine Learning Pipelines with Fine-grained Lineage. HPDC Zhao Zhang, Evan Randall Sparks, Michael J. Franklin
2017	A*	`conf`	KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. ICDE Evan Randall Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht
2017	—	`conf`	Paleo: A Performance Model for Deep Neural Networks. ICLR (Poster) Hang Qi, Evan Randall Sparks, Ameet Talwalkar
2017	A	`conf`	Random projection design for scalable implicit smoothing of randomly observed stochastic processes. AISTATS Francois Belletti, Evan Randall Sparks, Alexandre M. Bayen, Joseph Gonzalez
2016	—	`—`	End-to-End Large Scale Machine Learning with KeystoneML. Evan Randall Sparks
2016	J	`jnl`	KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. CoRR Evan Randall Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht
2016	J	`jnl`	MLlib: Machine Learning in Apache Spark. J. Mach. Learn. Res. 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
2016	A*	`conf`	Matrix Computations and Optimization in Apache Spark. KDD Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Aaron Staple, Matei Zaharia
2016	J	`jnl`	Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies. CoRR Francois W. Belletti, Evan Randall Sparks, Michael J. Franklin, Alexandre M. Bayen, Joseph E. Gonzalez
2015	—	`conf`	Automating model search for large scale machine learning. SoCC Evan Randall Sparks, Ameet Talwalkar, Daniel Haas, Michael J. Franklin, Michael I. Jordan, Tim Kraska
2015	J	`jnl`	Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems. CoRR Francois Belletti, Evan Randall Sparks, Michael J. Franklin, Alexandre M. Bayen
2015	J	`jnl`	MLlib: Machine Learning in Apache Spark. CoRR 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
2015	J	`jnl`	Scientific Computing Meets Big Data Technology: An Astronomy Use Case. CoRR Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
2015	—	`conf`	Scientific computing meets big data technology: An astronomy use case. IEEE BigData Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
2015	J	`jnl`	TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries. CoRR Evan Randall Sparks, Ameet Talwalkar, Michael J. Franklin, Michael I. Jordan, Tim Kraska
2015	J	`jnl`	linalg: Matrix Computations in Apache Spark. CoRR Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Alexander Ulanov, Matei Zaharia
2013	A*	`conf`	MLI: An API for Distributed Machine Learning. ICDM Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska
2013	J	`jnl`	MLI: An API for Distributed Machine Learning. CoRR Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska
2008	—	`conf`	TOCTOU, Traps, and Trusted Computing. TRUST Sergey Bratus, Nihal D'Cunha, Evan Randall Sparks, Sean W. Smith