Eldar Kurtic

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 23

Top Topics

Language Models For Information Retrieval

Avoid Overfitting

Top Venues

Publications

Abhinav Agarwalla, Abhay Gupta, Alexandre Marques, Shubhra Pandit, Michael Goin, Eldar Kurtic, Kevin Leong, Tuan Nguyen, Mahmoud Salem, Dan Alistarh, Sean Lie, Mark Kurtz
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment. CoRR (2024)
Ionut-Vlad Modoranu, Mher Safaryan, Grigory Malinovsky, Eldar Kurtic, Thomas Robert, Peter Richtárik, Dan Alistarh
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence. CoRR (2024)
Eldar Kurtic, Amir Moeini, Dan Alistarh
Mathador-LM: A Dynamic Benchmark for Mathematical Reasoning on Large Language Models. CoRR (2024)
Armand Nicolicioiu, Eugenia Iofinova, Eldar Kurtic, Mahdi Nikdan, Andrei Panferov, Ilia Markov, Nir Shavit, Dan Alistarh
Panza: A Personalized Text Writing Assistant via Data Playback and Local Fine-Tuning. CoRR (2024)
Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh
Accurate Neural Network Pruning Requires Rethinking Sparse Optimization. Trans. Mach. Learn. Res. 2024 (2024)
Eldar Kurtic, Elias Frantar, Dan Alistarh
ZipLM: Hardware-Aware Structured Pruning of Language Models. CoRR (2023)
Ionut-Vlad Modoranu, Aleksei Kalinov, Eldar Kurtic, Dan Alistarh
Error Feedback Can Accurately Compress Preconditioners. CoRR (2023)
Mahdi Nikdan, Tommaso Pegolotti, Eugenia Iofinova, Eldar Kurtic, Dan Alistarh
SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks. CoRR (2023)
Mahdi Nikdan, Tommaso Pegolotti, Eugenia Iofinova, Eldar Kurtic, Dan Alistarh
SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge. ICML (2023)
Denis Kuznedelev, Soroush Tabesh, Kimia Noorbakhsh, Elias Frantar, Sara Beery, Eldar Kurtic, Dan Alistarh
Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression. CoRR (2023)
Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models. NeurIPS (2023)
Eldar Kurtic, Elias Frantar, Dan Alistarh
ZipLM: Inference-Aware Structured Pruning of Language Models. NeurIPS (2023)
Eldar Kurtic, Torsten Hoefler, Dan Alistarh
How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry" Benchmark. CoRR (2023)
Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh
Accurate Neural Network Pruning Requires Rethinking Sparse Optimization. CoRR (2023)
Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh
CrAM: A Compression-Aware Minimizer. ICLR (2023)
Eldar Kurtic, Denis Kuznedelev, Elias Frantar, Michael Goin, Dan Alistarh
Sparse Fine-tuning for Inference Acceleration of Large Language Models. CoRR (2023)
Eldar Kurtic, Dan Alistarh
GMP*: Well-Tuned Global Magnitude Pruning Can Outperform Most BERT-Pruning Methods. CoRR (2022)
Eldar Kurtic, Daniel Campos, Tuan Nguyen, Elias Frantar, Mark Kurtz, Benjamin Fineran, Michael Goin, Dan Alistarh
The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models. CoRR (2022)
Zlatan Ajanovic, Emina Alickovic, Aida Brankovic, Sead Delalic, Eldar Kurtic, Salem Malikic, Adnan Mehonic, Hamza Merzic, Kenan Sehic, Bahrudin Trbalic
Vision for Bosnia and Herzegovina in Artificial Intelligence Age: Global Trends, Potential Opportunities, Selected Use-cases and Realistic Goals. CoRR (2022)
Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh
oViT: An Accurate Second-Order Pruning Framework for Vision Transformers. CoRR (2022)
Eldar Kurtic, Daniel Campos, Tuan Nguyen, Elias Frantar, Mark Kurtz, Benjamin Fineran, Michael Goin, Dan Alistarh
The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models. EMNLP (2022)
Elias Frantar, Eldar Kurtic, Dan Alistarh
Efficient Matrix-Free Approximations of Second-Order Information, with Applications to Pruning and Optimization. CoRR (2021)
Elias Frantar, Eldar Kurtic, Dan Alistarh
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information. NeurIPS (2021)