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Utku Evci
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2020 – today
- 2024
- [c14]Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci:
Scaling Laws for Sparsely-Connected Foundation Models. ICLR 2024 - [c13]Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou:
Dynamic Sparse Training with Structured Sparsity. ICLR 2024 - [i19]Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna:
Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers. CoRR abs/2402.04744 (2024) - [i18]Aleksandra Irena Nowak, Otniel-Bogdan Mercea, Anurag Arnab, Jonas Pfeiffer, Yann N. Dauphin, Utku Evci:
Towards Optimal Adapter Placement for Efficient Transfer Learning. CoRR abs/2410.15858 (2024) - 2023
- [c12]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. ICML 2023: 7480-7512 - [c11]Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci:
The Dormant Neuron Phenomenon in Deep Reinforcement Learning. ICML 2023: 32145-32168 - [i17]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang
, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i16]Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci:
The Dormant Neuron Phenomenon in Deep Reinforcement Learning. CoRR abs/2302.12902 (2023) - [i15]Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan S. Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci:
JaxPruner: A concise library for sparsity research. CoRR abs/2304.14082 (2023) - [i14]Mike Lasby
Dynamic Sparse Training with Structured Sparsity. CoRR abs/2305.02299 (2023) - [i13]Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci:
Scaling Laws for Sparsely-Connected Foundation Models. CoRR abs/2309.08520 (2023) - 2022
- [c10]Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin:
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win. AAAI 2022: 6577-6586 - [c9]Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov:
GradMax: Growing Neural Networks using Gradient Information. ICLR 2022 - [c8]Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer:
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. ICML 2022: 6009-6033 - [c7]Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro:
The State of Sparse Training in Deep Reinforcement Learning. ICML 2022: 7766-7792 - [i12]Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer:
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. CoRR abs/2201.03529 (2022) - [i11]Utku Evci, Max Vladymyrov, Thomas Unterthiner, Bart van Merriënboer, Fabian Pedregosa:
GradMax: Growing Neural Networks using Gradient Information. CoRR abs/2201.05125 (2022) - [i10]Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro:
The State of Sparse Training in Deep Reinforcement Learning. CoRR abs/2206.10369 (2022) - [i9]Sheng-Chun Kao, Amir Yazdanbakhsh, Suvinay Subramanian, Shivani Agrawal, Utku Evci, Tushar Krishna:
Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask. CoRR abs/2209.07617 (2022) - 2021
- [c6]Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves:
Practical Real Time Recurrent Learning with a Sparse Approximation. ICLR 2021 - [c5]Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle:
A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches. NeurIPS Datasets and Benchmarks 2021 - [i8]Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle:
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark. CoRR abs/2104.02638 (2021) - 2020
- [c4]Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle:
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. ICLR 2020 - [c3]Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen:
Rigging the Lottery: Making All Tickets Winners. ICML 2020: 2943-2952 - [i7]Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves:
A Practical Sparse Approximation for Real Time Recurrent Learning. CoRR abs/2006.07232 (2020) - [i6]Utku Evci, Yani Andrew Ioannou
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win. CoRR abs/2010.03533 (2020)
2010 – 2019
- 2019
- [i5]Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen:
The Difficulty of Training Sparse Neural Networks. CoRR abs/1906.10732 (2019) - [i4]Lakshay Sharma, Laura Graesser, Nikita Nangia, Utku Evci:
Natural Language Understanding with the Quora Question Pairs Dataset. CoRR abs/1907.01041 (2019) - [i3]Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen:
Rigging the Lottery: Making All Tickets Winners. CoRR abs/1911.11134 (2019) - 2018
- [c2]Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou:
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. ICLR (Workshop) 2018 - [i2]Utku Evci:
Detecting Dead Weights and Units in Neural Networks. CoRR abs/1806.06068 (2018) - 2017
- [i1]Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou:
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. CoRR abs/1706.04454 (2017) - 2016
- [c1]Ronan Boulic, Utku Evci, Eray Molla, Phanindra Pisupati:
One Step from the Locomotion to the Stepping Pattern. CASA 2016: 165-168
Coauthor Index
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last updated on 2024-11-27 21:20 CET by the dblp team
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