Benoit Steiner

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 32

Top Topics

Integer Solution

Top Venues

Publications

Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems. ICML (2023)
Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Pengtao Xie, Hugh Leather, Yuandong Tian
Learning to compile smartly for program size reduction. CoRR (2023)
Benoit Steiner, Mostafa Elhoushi, Jacob Kahn, James Hegarty
MODeL: Memory Optimizations for Deep Learning. ICML (2023)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. CoRR (2023)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Local Branching Relaxation Heuristics for Integer Linear Programs. CPAIOR (2023)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. ICML (2023)
Tamera Lanham, Anna Chen, Ansh Radhakrishnan, Benoit Steiner, Carson Denison, Danny Hernandez, Dustin Li, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamile Lukosiute, Karina Nguyen, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Robin Larson, Sam McCandlish, Sandipan Kundu, Saurav Kadavath, Shannon Yang, Thomas Henighan, Timothy Maxwell, Timothy Telleen-Lawton, Tristan Hume, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, Ethan Perez
Measuring Faithfulness in Chain-of-Thought Reasoning. CoRR (2023)
Roger B. Grosse, Juhan Bae, Cem Anil, Nelson Elhage, Alex Tamkin, Amirhossein Tajdini, Benoit Steiner, Dustin Li, Esin Durmus, Ethan Perez, Evan Hubinger, Kamile Lukosiute, Karina Nguyen, Nicholas Joseph, Sam McCandlish, Jared Kaplan, Samuel R. Bowman
Studying Large Language Model Generalization with Influence Functions. CoRR (2023)
Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. ICML (2023)
Jacob Kahn, Vineel Pratap, Tatiana Likhomanenko, Qiantong Xu, Awni Hannun, Jeff Cai, Paden Tomasello, Ann Lee, Edouard Grave, Gilad Avidov, Benoit Steiner, Vitaliy Liptchinsky, Gabriel Synnaeve, Ronan Collobert
Flashlight: Enabling Innovation in Tools for Machine Learning. CoRR (2022)
Shikhar Singh, James Hegarty, Hugh Leather, Benoit Steiner
A graph neural network-based performance model for deep learning applications. MAPS@PLDI (2022)
Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems. CoRR (2022)
Jacob D. Kahn, Vineel Pratap, Tatiana Likhomanenko, Qiantong Xu, Awni Y. Hannun, Jeff Cai, Paden Tomasello, Ann Lee, Edouard Grave, Gilad Avidov, Benoit Steiner, Vitaliy Liptchinsky, Gabriel Synnaeve, Ronan Collobert
Flashlight: Enabling Innovation in Tools for Machine Learning. ICML (2022)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Local Branching Relaxation Heuristics for Integer Linear Programs. CoRR (2022)
Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather, Aleksandar Zlateski
LoopStack: a Lightweight Tensor Algebra Compiler Stack. CoRR (2022)
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. CGO (2022)
Benoit Steiner, Mostafa Elhoushi, Jacob Kahn, James Hegarty
OLLA: Decreasing the Memory Usage of Neural Networks by Optimizing the Lifetime and Location of Arrays. CoRR (2022)
Shikhar Singh, Benoit Steiner, James Hegarty, Hugh Leather
Using Graph Neural Networks to model the performance of Deep Neural Networks. CoRR (2021)
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. CoRR (2021)
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
Learning Space Partitions for Path Planning. CoRR (2021)
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
Learning Space Partitions for Path Planning. NeurIPS (2021)
Benoit Steiner, Chris Cummins, Horace He, Hugh Leather
Value Learning for Throughput Optimization of Deep Learning Workloads. MLSys (2021)
Benoit Steiner, Chris Cummins, Horace He, Hugh Leather
Value Function Based Performance Optimization of Deep Learning Workloads. CoRR (2020)
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala
PyTorch: An Imperative Style, High-Performance Deep Learning Library. CoRR (2019)
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala
PyTorch: An Imperative Style, High-Performance Deep Learning Library. NeurIPS (2019)
Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michaël Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Frédo Durand, Jonathan Ragan-Kelley
Learning to optimize halide with tree search and random programs. ACM Trans. Graph. 38 (4) (2019)
Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean
A Hierarchical Model for Device Placement. ICLR (Poster) (2018)
Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean
Device Placement Optimization with Reinforcement Learning. CoRR (2017)
Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean
Device Placement Optimization with Reinforcement Learning. ICML (2017)
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. CoRR (2016)
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng
TensorFlow: A System for Large-Scale Machine Learning. OSDI (2016)
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang
TensorFlow: A system for large-scale machine learning. CoRR (2016)