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Kunle Olukotun

Stanford University

Prior-guided Bayesian Optimization

Jun 25, 2020
Artur Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter


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Taurus: An Intelligent Data Plane

Feb 12, 2020
Tushar Swamy, Alexander Rucker, Muhammad Shahbaz, Kunle Olukotun

* 12 pages, 13 figures, and 6 tables 

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Serving Recurrent Neural Networks Efficiently with a Spatial Accelerator

Sep 26, 2019
Tian Zhao, Yaqi Zhang, Kunle Olukotun

* Proceedings of the 2 nd SysML Conference, Palo Alto, CA, USA, 2019. Copyright 2019 by the author(s) 

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Polystore++: Accelerated Polystore System for Heterogeneous Workloads

May 24, 2019
Rekha Singhal, Nathan Zhang, Luigi Nardi, Muhammad Shahbaz, Kunle Olukotun

* ICDCS 2019 
* 11 pages, Accepted in ICDCS 2019 

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DeepFreak: Learning Crystallography Diffraction Patterns with Automated Machine Learning

May 03, 2019
Artur Souza, Leonardo B. Oliveira, Sabine Hollatz, Matt Feldman, Kunle Olukotun, James M. Holton, Aina E. Cohen, Luigi Nardi


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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros 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 Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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Practical Design Space Exploration

Oct 11, 2018
Luigi Nardi, David Koeplinger, Kunle Olukotun


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Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark

Jun 04, 2018
Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Chris Re, Matei Zaharia


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High-Accuracy Low-Precision Training

Mar 09, 2018
Christopher De Sa, Megan Leszczynski, Jian Zhang, Alana Marzoev, Christopher R. Aberger, Kunle Olukotun, Christopher Ré


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Infrastructure for Usable Machine Learning: The Stanford DAWN Project

Jun 09, 2017
Peter Bailis, Kunle Olukotun, Christopher Re, Matei Zaharia


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Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling

Jun 16, 2016
Christopher De Sa, Kunle Olukotun, Christopher Ré


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Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width

Oct 02, 2015
Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré


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Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms

Oct 02, 2015
Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré


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Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems

Feb 10, 2015
Christopher De Sa, Kunle Olukotun, Christopher Ré


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Utilizing Static Analysis and Code Generation to Accelerate Neural Networks

Jun 27, 2012
Lawrence McAfee, Kunle Olukotun

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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