Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
144 Publications
2024 | Published | Conference Paper | IST-REx-ID: 18975 |

Modoranu, Ionut-Vlad, et al. “Error Feedback Can Accurately Compress Preconditioners.” 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 35910–33.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18976 |

Islamov, Rustem, et al. “AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms.” Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, vol. 238, ML Research Press, 2024, pp. 649–57.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18977 |

Dettmers, Tim, et al. “SpQR: A Sparse-Quantized Representation for near-Lossless LLM Weight Compression.” 12th International Conference on Learning Representations, OpenReview, 2024.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 17093 |

Zakerinia, Hossein, et al. “Communication-Efficient Federated Learning with Data and Client Heterogeneity.” Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, vol. 238, ML Research Press, 2024, pp. 3448–56.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 17329 |

Alistarh, Dan-Adrian, et al. “Game Dynamics and Equilibrium Computation in the Population Protocol Model.” Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2024, pp. 40–49, doi:10.1145/3662158.3662768.
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 17332 |

Kokorin, Ilya, et al. “Wait-Free Trees with Asymptotically-Efficient Range Queries.” 2024 IEEE International Parallel and Distributed Processing Symposium, IEEE, 2024, pp. 169–79, doi:10.1109/IPDPS57955.2024.00023.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 17456 |

Markov, Ilia, et al. “L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient Data-Parallel Deep Learning.” Proceedings of Machine Learning and Systems , edited by P. Gibbons et al., vol. 6, Association for Computing Machinery, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2024 | Published | Thesis | IST-REx-ID: 17485 |

Frantar, Elias. Compressing Large Neural Networks : Algorithms, Systems and Scaling Laws. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17485.
[Published Version]
View
| Files available
| DOI
2024 | Published | Thesis | IST-REx-ID: 17490 |

Markov, Ilia. Communication-Efficient Distributed Training of Deep Neural Networks: An Algorithms and Systems Perspective. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17490.
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 15011 |

Kurtic, Eldar, et al. “How to Prune Your Language Model: Recovering Accuracy on the ‘Sparsity May Cry’ Benchmark.” Proceedings of Machine Learning Research, vol. 234, ML Research Press, 2024, pp. 542–53.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18061 |

Frantar, Elias, and Dan-Adrian Alistarh. “QMoE: Sub-1-Bit Compression of Trillion Parameter Models.” Proceedings of Machine Learning and Systems, edited by P. Gibbons et al., vol. 6, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
2024 | Published | Conference Paper | IST-REx-ID: 18062 |

Frantar, Elias, et al. “Scaling Laws for Sparsely-Connected Foundation Models.” The Twelfth International Conference on Learning Representations, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18070
Chatterjee, Bapi, et al. “Federated SGD with Local Asynchrony.” Proceedings of the 44th International Conference on Distributed Computing Systems, IEEE, 2024, pp. 857–68, doi:10.1109/ICDCS60910.2024.00084.
View
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 18113 |

Egiazarian, Vage, et al. “Extreme Compression of Large Language Models via Additive Quantization.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 12284–303.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18117 |

Nikdan, Mahdi, et al. “RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 38187–206.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18121 |

Moakhar, Arshia Soltani, et al. “SPADE: Sparsity-Guided Debugging for Deep Neural Networks.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 45955–87.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2024 | Published | Thesis | IST-REx-ID: 17465 |

Shevchenko, Alexander. High-Dimensional Limits in Artificial Neural Networks. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17465.
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 17469 |

Kögler, Kevin, et al. “Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 24964–5015.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2023 | Published | Journal Article | IST-REx-ID: 13179 |

Koval, Nikita, et al. “CQS: A Formally-Verified Framework for Fair and Abortable Synchronization.” Proceedings of the ACM on Programming Languages, vol. 7, 116, Association for Computing Machinery , 2023, doi:10.1145/3591230.
[Published Version]
View
| Files available
| DOI
2023 | Published | Conference Paper | IST-REx-ID: 13262 |

Fedorov, Alexander, et al. “Provably-Efficient and Internally-Deterministic Parallel Union-Find.” Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2023, pp. 261–71, doi:10.1145/3558481.3591082.
[Published Version]
View
| Files available
| DOI
| arXiv