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156 Publications
2025 | Published | Journal Article | IST-REx-ID: 19713 | 
Talaei, Shayan, et al. “Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence.” Proceedings of The39th AAAI Conference on Artificial Intelligence, vol. 39, no. 19, Association for the Advancement of Artificial Intelligence, 2025, pp. 20778–86, doi:10.1609/aaai.v39i19.34290.
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2025 | Published | Conference Paper | IST-REx-ID: 19877 |
Frantar, Elias, et al. “MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models.” Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2025, pp. 239–51, doi:10.1145/3710848.3710871.
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2025 | Epub ahead of print | Journal Article | IST-REx-ID: 19969 |
Alistarh, Dan-Adrian, et al. “Near-Optimal Leader Election in Population Protocols on Graphs.” Distributed Computing, Springer Nature, 2025, doi:10.1007/s00446-025-00487-7.
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2025 | Published | Conference Paper | IST-REx-ID: 20038 |
Jin, Tian, et al. “The Journey Matters: Average Parameter Count over Pre-Training Unifies Sparse and Dense Scaling Laws.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 85165–81.
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2025 | Published | Conference Paper | IST-REx-ID: 20037 |
Sawmya, Shashata, et al. “Wasserstein Distances, Neuronal Entanglement, and Sparsity.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 26244–74.
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2025 | Published | Conference Paper | IST-REx-ID: 20032 |
Chen, Jiale, et al. “Scalable Mechanistic Neural Networks.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 63716–37.
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2025 | Published | Conference Paper | IST-REx-ID: 20034 |
Robert, Thomas, et al. “LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 101877–913.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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