Alban Desmaison

According to our database, Alban Desmaison authored at least 22 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Dr. DNA: Combating Silent Data Corruptions in Deep Learning using Distribution of Neuron Activations.

Dongning Ma, Fan Fred Lin, Alban Desmaison, Joel Coburn, Daniel Moore, Sriram Sankar, Xun Jiao

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation.

Jason Ansel, Edward Z. Yang, Horace He, Natalia Gimelshein, Animesh Jain, Michael Voznesensky, Bin Bao, Peter Bell, David Berard, Evgeni Burovski, Geeta Chauhan, Anjali Chourdia, Will Constable, Alban Desmaison, Zachary DeVito, Elias Ellison, Will Feng, Jiong Gong, Michael Gschwind, Brian Hirsh, Sherlock Huang, Kshiteej Kalambarkar, Laurent Kirsch, Michael Lazos, Mario Lezcano, Yanbo Liang, Jason Liang, Yinghai Lu, C. K. Luk, Bert Maher, Yunjie Pan, Christian Puhrsch, Matthias Reso, Mark Saroufim, Marcos Yukio Siraichi, Helen Suk, Shunting Zhang, Michael Suo, Phil Tillet, Xu Zhao, Eikan Wang, Keren Zhou, Richard Zou, Xiaodong Wang, Ajit Mathews, William Wen, Gregory Chanan, Peng Wu, Soumith Chintala

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

Yanli Zhao, Andrew Gu, Rohan Varma, Liang Luo, Chien-Chin Huang, Min Xu, Less Wright, Hamid Shojanazeri, Myle Ott, Sam Shleifer, Alban Desmaison, Can Balioglu, Pritam Damania, Bernard Nguyen, Geeta Chauhan, Yuchen Hao, Ajit Mathews, Shen Li

Proc. VLDB Endow., 2023

Evaluating and Enhancing Robustness of Deep Recommendation Systems Against Hardware Errors.

Dongning Ma, Xun Jiao, Fan Fred Lin, Mengshi Zhang, Alban Desmaison, Thomas Sellinger, Daniel Moore, Sriram Sankar

CoRR, 2023

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

Yanli Zhao, Andrew Gu, Rohan Varma, Liang Luo, Chien-Chin Huang, Min Xu, Less Wright, Hamid Shojanazeri, Myle Ott, Sam Shleifer, Alban Desmaison, Can Balioglu, Bernard Nguyen, Geeta Chauhan, Yuchen Hao, Shen Li

CoRR, 2023

Brief Industry Paper: Evaluating Robustness of Deep Learning-Based Recommendation Systems Against Hardware Errors: A Case Study.

Xun Jiao, Fan Fred Lin, Matt Xiao, Alban Desmaison, Daniel Moore, Sriram Sankar

Proceedings of the IEEE Real-Time Systems Symposium, 2023

PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls.

Shen Li, Pritam Damania, Luca Wehrstedt, Rohan Varma, Omkar Salpekar, Pavel Belevich, Howard Huang, Yanli Zhao, Lucas Hosseini, Wanchao Liang, Hongyi Jia, Shihao Xu, Satendra Gera, Alisson G. Azzolini, Guoqiang Jerry Chen, Zachary DeVito, Chaoyang He, Amir Ziashahabi, Alban Desmaison, Edward Z. Yang, Gregory Chanan, Brian Vaughan, Manoj Krishnan, Joseph S. Spisak, Salman Avestimehr, Soumith Chintala

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

2021

Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition.

Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

CoRR, 2021

2020

Lagrangian Decomposition for Neural Network Verification.

Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Optimization for, and by, machine learning.

Alban Desmaison

PhD thesis, 2019

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials.

Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

SIAM J. Imaging Sci., 2019

PyTorch: An Imperative Style, High-Performance Deep Learning Library.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017

Learning Disentangled Representations with Semi-Supervised Deep Generative Models.

Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning to superoptimize programs.

Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli

Proceedings of the 5th International Conference on Learning Representations, 2017

Efficient Linear Programming for Dense CRFs.

Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Inducing Interpretable Representations with Variational Autoencoders.

N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr

CoRR, 2016

Learning to superoptimize programs - Workshop Version.

Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli

CoRR, 2016

Playing Doom with SLAM-Augmented Deep Reinforcement Learning.

Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth, Philip H. S. Torr

CoRR, 2016

Adaptive Neural Compilation.

Rudy Bunel, Alban Desmaison, Pawan Kumar Mudigonda, Pushmeet Kohli, Philip H. S. Torr

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Efficient Continuous Relaxations for Dense CRF.

Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the Computer Vision - ECCV 2016, 2016

2014

Power Consumption Analysis of Parallel Algorithms on GPUs.

Frédéric Magoulès, Abal-Kassim Cheik Ahamed, Alban Desmaison, Jean-Christophe Léchenet, François Mayer, Haifa Ben Salem, Thomas Zhu

Proceedings of the 2014 IEEE International Conference on High Performance Computing and Communications, 2014

Fast and Green Computing with Graphics Processing Units for Solving Sparse Linear Systems.

Abal-Kassim Cheik Ahamed, Alban Desmaison, Frédéric Magoulès

Proceedings of the 2014 IEEE International Conference on High Performance Computing and Communications, 2014