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34 Publications
2024 | Published | Conference Paper | IST-REx-ID: 18972 | 
Bombari, Simone, and Marco Mondelli. “How Spurious Features Are Memorized: Precise Analysis for Random and NTK Features.” In 41st International Conference on Machine Learning, 235:4267–99. ML Research Press, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18115 |
Axiotis, Kyriakos, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David P. Woodruff, and Michael Wunder. “Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond.” In Proceedings of the 41st International Conference on Machine Learning, 235:2086–2107. ML Research Press, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18116 |
La Tour, Max Dupré, Monika Henzinger, and David Saulpic. “Making Old Things New: A Unified Algorithm for Differentially Private Clustering.” In Proceedings of the 41st International Conference on Machine Learning, 235:12046–86. ML Research Press, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18121 |
Moakhar, Arshia Soltani, Eugenia B Iofinova, Elias Frantar, and Dan-Adrian Alistarh. “SPADE: Sparsity-Guided Debugging for Deep Neural Networks.” In Proceedings of the 41st International Conference on Machine Learning, 235:45955–87. ML Research Press, 2024.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14460 |
Nikdan, Mahdi, Tommaso Pegolotti, Eugenia B Iofinova, Eldar Kurtic, and Dan-Adrian Alistarh. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” In Proceedings of the 40th International Conference on Machine Learning, 202:26215–27. ML Research Press, 2023.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14458 |
Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14461 |
Markov, Ilia, Adrian Vladu, Qi Guo, and Dan-Adrian Alistarh. “Quantized Distributed Training of Large Models with Convergence Guarantees.” In Proceedings of the 40th International Conference on Machine Learning, 202:24020–44. ML Research Press, 2023.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14462 |
Fichtenberger, Hendrik, Monika Henzinger, and Jalaj Upadhyay. “Constant Matters: Fine-Grained Error Bound on Differentially Private Continual Observation.” In Proceedings of the 40th International Conference on Machine Learning, 202:10072–92. ML Research Press, 2023.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko, Alexander, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 13241 |
Konstantinov, Nikola H, and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” In Proceedings of Machine Learning Research, 171:59–83. ML Research Press, 2022.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 13239 |
Van Der Plas, Thijs L., Tim P Vogels, and Sanjay G. Manohar. “Predictive Learning Enables Neural Networks to Learn Complex Working Memory Tasks.” In Proceedings of Machine Learning Research, 199:518–31. ML Research Press, 2022.
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2021 | Published | Conference Paper | IST-REx-ID: 13147 |
Alimisis, Foivos, Peter Davies, and Dan-Adrian Alistarh. “Communication-Efficient Distributed Optimization with Quantized Preconditioners.” In Proceedings of the 38th International Conference on Machine Learning, 139:196–206. ML Research Press, 2021.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 13146 |
Nguyen, Quynh, Marco Mondelli, and Guido Montufar. “Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks.” In Proceedings of the 38th International Conference on Machine Learning, 139:8119–29. ML Research Press, 2021.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 11651 |
Wang, Di, Kimon Fountoulakis, Monika Henzinger, Michael W. Mahoney, and Satish Rao . “Capacity Releasing Diffusion for Speed and Locality.” In Proceedings of the 34th International Conference on Machine Learning, 70:3598–3607. ML Research Press, 2017.
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| arXiv