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756 Publications
2024 |
Published |
Journal Article |
IST-REx-ID: 17203 |
C. Hafner, M. Ly, and C. Wojtan, “Spin-it faster: Quadrics solve all topology optimization problems that depend only on mass moments,” Transactions on Graphics, vol. 43, no. 4. Association for Computing Machinery, 2024.
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2024 |
Published |
Journal Article |
IST-REx-ID: 15313 |
L. N. Agasthya and C. J. Muller, “Dynamics and scaling of internally cooled convection,” Communications in Nonlinear Science and Numerical Simulation, vol. 134. Elsevier, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17411 |
J. A. Scott, H. Zakerinia, and C. Lampert, “PEFLL: Personalized federated learning by learning to learn,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18120 |
J. A. Scott and Á. Cahill, “Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 44012–44037.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18118 |
H. Zakerinia, A. Behjati, and C. Lampert, “More flexible PAC-Bayesian meta-learning by learning learning algorithms,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 58122–58139.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17332 |
I. Kokorin, V. Yudov, V. Aksenov, and D.-A. Alistarh, “Wait-free trees with asymptotically-efficient range queries,” in 2024 IEEE International Parallel and Distributed Processing Symposium, San Francisco, CA, United States, 2024, pp. 169–179.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 15011 |
E. Kurtic, T. Hoefler, and D.-A. Alistarh, “How to prune your language model: Recovering accuracy on the ‘Sparsity May Cry’ benchmark,” in Proceedings of Machine Learning Research, Hongkong, China, 2024, vol. 234, pp. 542–553.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17329 |
D.-A. Alistarh, K. Chatterjee, M. Karrabi, and J. M. Lazarsfeld, “Game dynamics and equilibrium computation in the population protocol model,” in Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing, Nantes, France, 2024, pp. 40–49.
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2024 |
Published |
Conference Paper |
IST-REx-ID: 18121 |
A. S. Moakhar, E. B. Iofinova, E. Frantar, and D.-A. Alistarh, “SPADE: Sparsity-guided debugging for deep neural networks,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 45955–45987.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18976 |
R. Islamov, M. Safaryan, and D.-A. Alistarh, “AsGrad: A sharp unified analysis of asynchronous-SGD algorithms,” in Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 2024, vol. 238, pp. 649–657.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18113 |
V. Egiazarian, A. Panferov, D. Kuznedelev, E. Frantar, A. Babenko, and D.-A. Alistarh, “Extreme compression of large language models via additive quantization,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 12284–12303.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18975 |
I.-V. Modoranu, A. Kalinov, E. Kurtic, E. Frantar, and D.-A. Alistarh, “Error feedback can accurately compress preconditioners,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 35910–35933.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18977 |
T. Dettmers et al., “SpQR: A sparse-quantized representation for near-lossless LLM weight compression,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17093 |
H. Zakerinia, S. Talaei, G. Nadiradze, and D.-A. Alistarh, “Communication-efficient federated learning with data and client heterogeneity,” in Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 2024, vol. 238, pp. 3448–3456.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18117 |
M. Nikdan, S. Tabesh, E. Crncevic, and D.-A. Alistarh, “RoSA: Accurate parameter-efficient fine-tuning via robust adaptation,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 38187–38206.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 15315 |
D. Brückner and C. P. Broedersz, “Learning dynamical models of single and collective cell migration: a review,” Reports on Progress in Physics, vol. 87, no. 5. IOP Publishing, 2024.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 15250 |
D. Boytsov et al., “Orphan lysosomal solute carrier MFSD1 facilitates highly selective dipeptide transport,” Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 13. National Academy of Sciences, 2024.
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2024 |
Published |
Journal Article |
IST-REx-ID: 15024 |
P. Robin, “Correlation-induced viscous dissipation in concentrated electrolytes,” Journal of Chemical Physics, vol. 160, no. 6. AIP Publishing, 2024.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 17892 |
F. Olmeda and S. Rulands, “Field theory of enzyme-substrate systems with restricted long-range interactions,” Physical Review E, vol. 110, no. 2. American Physical Society, 2024.
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