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117 Publications


2024 | Conference Paper | IST-REx-ID: 15011 | OA
Kurtic E, Hoefler T, Alistarh D-A. How to prune your language model: Recovering accuracy on the “Sparsity May Cry” benchmark. In: Proceedings of Machine Learning Research. Vol 234. ML Research Press; 2024:542-553.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 12735 | OA
Koval N, Alistarh D-A, Elizarov R. Fast and scalable channels in Kotlin Coroutines. In: Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery; 2023:107-118. doi:10.1145/3572848.3577481
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Poster | IST-REx-ID: 12736 | OA
Aksenov V, Brown TA, Fedorov A, Kokorin I. Unexpected Scaling in Path Copying Trees. Association for Computing Machinery; 2023:438-440. doi:10.1145/3572848.3577512
[Published Version] View | DOI | Download Published Version (ext.)
 

2023 | Conference Paper | IST-REx-ID: 13053 | OA
Peste E-A, Vladu A, Kurtic E, Lampert C, Alistarh D-A. CrAM: A Compression-Aware Minimizer. In: 11th International Conference on Learning Representations .
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 13179 | OA
Koval N, Khalanskiy D, Alistarh D-A. CQS: A formally-verified framework for fair and abortable synchronization. Proceedings of the ACM on Programming Languages. 2023;7. doi:10.1145/3591230
[Published Version] View | Files available | DOI
 

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