Alban Desmaison

32 papers A* 2A 2Journal 18Unranked 9

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Dr. DNA: Combating Silent Data Corruptions in Deep Learning using Distribution of Neuron Activations. ASPLOS (3) Dongning Ma, Fan Fred Lin, Alban Desmaison, Joel Coburn, Daniel Moore, Sriram Sankar, Xun Jiao
2024	—	`conf`	PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation. ASPLOS (2) 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
2023	A	`conf`	Brief Industry Paper: Evaluating Robustness of Deep Learning-Based Recommendation Systems Against Hardware Errors: A Case Study. RTSS Xun Jiao, Fan Fred Lin, Matt Xiao, Alban Desmaison, Daniel Moore, Sriram Sankar
2023	J	`jnl`	Evaluating and Enhancing Robustness of Deep Recommendation Systems Against Hardware Errors. CoRR Dongning Ma, Xun Jiao, Fan Fred Lin, Mengshi Zhang, Alban Desmaison, Thomas Sellinger, Daniel Moore, Sriram Sankar
2023	J	`jnl`	PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. CoRR 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
2023	J	`jnl`	PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. Proc. VLDB Endow. 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
2023	—	`conf`	PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. MLSys 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
2021	J	`jnl`	Fast and Green Computing with Graphics Processing Units for solving Sparse Linear Systems. CoRR Abal-Kassim Cheik Ahamed, Alban Desmaison, Frédéric Magoulès
2021	J	`jnl`	Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. CoRR Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2021	J	`jnl`	Power Consumption Analysis of Parallel Algorithms on GPUs. CoRR Frédéric Magoulès, Abal-Kassim Cheik Ahamed, Alban Desmaison, Jean-Christophe Léchenet, François Mayer, Haifa Ben Salem, Thomas Zhu
2020	A	`conf`	Lagrangian Decomposition for Neural Network Verification. UAI Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2020	J	`jnl`	Lagrangian Decomposition for Neural Network Verification. CoRR Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2019	J	`jnl`	Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials. SIAM J. Imaging Sci. Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2019	—	`—`	Optimization for, and by, machine learning. Alban Desmaison
2019	A*	`conf`	PyTorch: An Imperative Style, High-Performance Deep Learning Library. NeurIPS 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
2019	J	`jnl`	PyTorch: An Imperative Style, High-Performance Deep Learning Library. CoRR 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
2018	J	`jnl`	Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials. CoRR Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2017	A*	`conf`	Efficient Linear Programming for Dense CRFs. CVPR Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar
2017	—	`conf`	Learning Disentangled Representations with Semi-Supervised Deep Generative Models. NIPS Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr
2017	J	`jnl`	Learning Disentangled Representations with Semi-Supervised Deep Generative Models. CoRR N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr
2017	—	`conf`	Learning to superoptimize programs. ICLR (Poster) Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli
2016	—	`conf`	Adaptive Neural Compilation. NIPS Rudy Bunel, Alban Desmaison, Pawan Kumar Mudigonda, Pushmeet Kohli, Philip H. S. Torr
2016	J	`jnl`	Adaptive Neural Compilation. CoRR Rudy Bunel, Alban Desmaison, Pushmeet Kohli, Philip H. S. Torr, Pawan Kumar Mudigonda
2016	—	`conf`	Efficient Continuous Relaxations for Dense CRF. ECCV (2) Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2016	J	`jnl`	Efficient Continuous Relaxations for Dense CRF. CoRR Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
2016	J	`jnl`	Efficient Linear Programming for Dense CRFs. CoRR Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar
2016	J	`jnl`	Inducing Interpretable Representations with Variational Autoencoders. CoRR N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr
2016	J	`jnl`	Learning to superoptimize programs - Workshop Version. CoRR Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli
2016	J	`jnl`	Learning to superoptimize programs. CoRR Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli
2016	J	`jnl`	Playing Doom with SLAM-Augmented Deep Reinforcement Learning. CoRR Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth, Philip H. S. Torr
2014	—	`conf`	Fast and Green Computing with Graphics Processing Units for Solving Sparse Linear Systems. HPCC/CSS/ICESS Abal-Kassim Cheik Ahamed, Alban Desmaison, Frédéric Magoulès
2014	—	`conf`	Power Consumption Analysis of Parallel Algorithms on GPUs. HPCC/CSS/ICESS Frédéric Magoulès, Abal-Kassim Cheik Ahamed, Alban Desmaison, Jean-Christophe Léchenet, François Mayer, Haifa Ben Salem, Thomas Zhu