Mark Kurtz

According to our database, Mark Kurtz authored at least 6 papers between 2020 and 2024.

Collaborative distances:

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

2024

Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment.

Abhinav Agarwalla, Abhay Gupta, Alexandre Marques, Shubhra Pandit, Michael Goin, Eldar Kurtic, Kevin Leong, Tuan Nguyen, Mahmoud Salem, Dan Alistarh, Sean Lie, Mark Kurtz

CoRR, 2024

2023

oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes.

Daniel Campos, Alexandre Marques, Mark Kurtz, ChengXiang Zhai

Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing, 2023

2022

Sparse*BERT: Sparse Models are Robust.

Daniel Campos, Alexandre Marques, Tuan Nguyen, Mark Kurtz, ChengXiang Zhai

CoRR, 2022

The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models.

Eldar Kurtic, Daniel Campos, Tuan Nguyen, Elias Frantar, Mark Kurtz, Benjamin Fineran, Michael Goin, Dan Alistarh

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

How Well Do Sparse ImageNet Models Transfer?

Eugenia Iofinova, Alexandra Peste, Mark Kurtz, Dan Alistarh

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2020

Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks.

Mark Kurtz, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William M. Leiserson, Sage Moore, Nir Shavit, Dan Alistarh

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