Utku Evci - RankMe

40 papers A* 12Journal 23Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Compression Scaling Laws:Unifying Sparsity and Quantization. CoRR Elias Frantar, Utku Evci, Wonpyo Park, Neil Houlsby, Dan Alistarh
2025	—	`conf`	Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers. CPAL Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna
2025	J	`jnl`	Spark Transformer: Reactivating Sparsity in FFN and Attention. CoRR Chong You, Kan Wu, Zhipeng Jia, Lin Chen, Srinadh Bhojanapalli, Jiaxian Guo, Utku Evci, Jan Wassenberg, Praneeth Netrapalli, Jeremiah J. Willcock, Suvinay Subramanian, Felix Chern, Alek Andreev, Shreya Pathak, Felix X. Yu, Prateek Jain, David E. Culler, Henry M. Levy, Sanjiv Kumar
2025	A*	`conf`	The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws. ICLR Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite
2025	J	`jnl`	The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws. CoRR Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite
2024	A*	`conf`	Dynamic Sparse Training with Structured Sparsity. ICLR Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou
2024	—	`conf`	Jaxpruner: A Concise Library for Sparsity Research. CPAL Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
2024	J	`jnl`	Learning Parameter Sharing with Tensor Decompositions and Sparsity. CoRR Cem Üyük, Mike Lasby, Mohamed Yassin, Utku Evci, Yani Ioannou
2024	J	`jnl`	Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers. CoRR Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna
2024	A*	`conf`	Scaling Laws for Sparsely-Connected Foundation Models. ICLR Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci
2024	J	`jnl`	Towards Optimal Adapter Placement for Efficient Transfer Learning. CoRR Aleksandra Irena Nowak, Otniel-Bogdan Mercea, Anurag Arnab, Jonas Pfeiffer, Yann N. Dauphin, Utku Evci
2023	J	`jnl`	Dynamic Sparse Training with Structured Sparsity. CoRR Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani A. Ioannou
2023	J	`jnl`	JaxPruner: A concise library for sparsity research. CoRR 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 J. C. Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
2023	J	`jnl`	Scaling Laws for Sparsely-Connected Foundation Models. CoRR Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci
2023	A*	`conf`	Scaling Vision Transformers to 22 Billion Parameters. ICML 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
2023	J	`jnl`	Scaling Vision Transformers to 22 Billion Parameters. CoRR 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
2023	A*	`conf`	The Dormant Neuron Phenomenon in Deep Reinforcement Learning. ICML Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci
2023	J	`jnl`	The Dormant Neuron Phenomenon in Deep Reinforcement Learning. CoRR Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci
2022	A*	`conf`	GradMax: Growing Neural Networks using Gradient Information. ICLR Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov
2022	J	`jnl`	GradMax: Growing Neural Networks using Gradient Information. CoRR Utku Evci, Max Vladymyrov, Thomas Unterthiner, Bart van Merriënboer, Fabian Pedregosa
2022	A*	`conf`	Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win. AAAI Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin
2022	A*	`conf`	Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. ICML Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
2022	J	`jnl`	Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. CoRR Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
2022	A*	`conf`	The State of Sparse Training in Deep Reinforcement Learning. ICML Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro
2022	J	`jnl`	The State of Sparse Training in Deep Reinforcement Learning. CoRR Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro
2022	J	`jnl`	Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask. CoRR Sheng-Chun Kao, Amir Yazdanbakhsh, Suvinay Subramanian, Shivani Agrawal, Utku Evci, Tushar Krishna
2021	—	`conf`	A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches. NeurIPS Datasets and Benchmarks Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
2021	J	`jnl`	Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark. CoRR Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
2021	A*	`conf`	Practical Real Time Recurrent Learning with a Sparse Approximation. ICLR Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
2020	J	`jnl`	A Practical Sparse Approximation for Real Time Recurrent Learning. CoRR Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
2020	J	`jnl`	Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win. CoRR Utku Evci, Yani Andrew Ioannou, Cem Keskin, Yann N. Dauphin
2020	A*	`conf`	Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. ICLR Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle
2020	A*	`conf`	Rigging the Lottery: Making All Tickets Winners. ICML Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
2019	J	`jnl`	Natural Language Understanding with the Quora Question Pairs Dataset. CoRR Lakshay Sharma, Laura Graesser, Nikita Nangia, Utku Evci
2019	J	`jnl`	Rigging the Lottery: Making All Tickets Winners. CoRR Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
2019	J	`jnl`	The Difficulty of Training Sparse Neural Networks. CoRR Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen
2018	J	`jnl`	Detecting Dead Weights and Units in Neural Networks. CoRR Utku Evci
2018	—	`conf`	Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. ICLR (Workshop) Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou
2017	J	`jnl`	Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. CoRR Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou
2016	—	`conf`	One Step from the Locomotion to the Stepping Pattern. CASA Ronan Boulic, Utku Evci, Eray Molla, Phanindra Pisupati