Utku Evci

According to our database, Utku Evci authored at least 24 papers between 2016 and 2024.

Collaborative distances:

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

2024

Learning Parameter Sharing with Tensor Decompositions and Sparsity.

Cem Üyük, Mike Lasby, Mohamed Yassin, Utku Evci, Yani Ioannou

CoRR, 2024

Towards Optimal Adapter Placement for Efficient Transfer Learning.

Aleksandra Irena Nowak, Otniel-Bogdan Mercea, Anurag Arnab, Jonas Pfeiffer, Yann N. Dauphin, Utku Evci

CoRR, 2024

Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers.

Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna

CoRR, 2024

Dynamic Sparse Training with Structured Sparsity.

Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Scaling Laws for Sparsely-Connected Foundation Models.

Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

JaxPruner: A concise library for sparsity research.

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

CoRR, 2023

The Dormant Neuron Phenomenon in Deep Reinforcement Learning.

Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci

Proceedings of the International Conference on Machine Learning, 2023

Scaling Vision Transformers to 22 Billion Parameters.

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

Proceedings of the International Conference on Machine Learning, 2023

2022

Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask.

Sheng-Chun Kao, Amir Yazdanbakhsh, Suvinay Subramanian, Shivani Agrawal, Utku Evci, Tushar Krishna

CoRR, 2022

The State of Sparse Training in Deep Reinforcement Learning.

Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro

Proceedings of the International Conference on Machine Learning, 2022

Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning.

Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer

Proceedings of the International Conference on Machine Learning, 2022

GradMax: Growing Neural Networks using Gradient Information.

Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov

Proceedings of the Tenth International Conference on Learning Representations, 2022

Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win.

Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark.

Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle

CoRR, 2021

A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches.

Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Practical Real Time Recurrent Learning with a Sparse Approximation.

Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

A Practical Sparse Approximation for Real Time Recurrent Learning.

Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves

CoRR, 2020

Rigging the Lottery: Making All Tickets Winners.

Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen

Proceedings of the 37th International Conference on Machine Learning, 2020

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples.

Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Natural Language Understanding with the Quora Question Pairs Dataset.

Lakshay Sharma, Laura Graesser, Nikita Nangia, Utku Evci

CoRR, 2019

The Difficulty of Training Sparse Neural Networks.

Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen

CoRR, 2019

2018

Detecting Dead Weights and Units in Neural Networks.

Utku Evci

CoRR, 2018

Empirical Analysis of the Hessian of Over-Parametrized Neural Networks.

Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou

Proceedings of the 6th International Conference on Learning Representations, 2018

2016

One Step from the Locomotion to the Stepping Pattern.

Ronan Boulic, Utku Evci, Eray Molla, Phanindra Pisupati

Proceedings of the 29th International Conference on Computer Animation and Social Agents, 2016