| Adalora: Adaptive budget allocation for parameter-efficient fine-tuning Q Zhang, M Chen, A Bukharin, N Karampatziakis, P He, Y Cheng, ... arXiv preprint arXiv:2303.10512, 2023 | 1100 | 2023 |
| An empirical evaluation of supervised learning in high dimensions R Caruana, N Karampatziakis, A Yessenalina Proceedings of the 25th international conference on Machine learning, 96-103, 2008 | 814 | 2008 |
| Gradient coding: Avoiding stragglers in distributed learning R Tandon, Q Lei, AG Dimakis, N Karampatziakis International Conference on Machine Learning, 3368-3376, 2017 | 639 | 2017 |
| Three-dimensional face recognition in the presence of facial expressions: An annotated deformable model approach IA Kakadiaris, G Passalis, G Toderici, MN Murtuza, Y Lu, ... IEEE Transactions on pattern analysis and machine intelligence 29 (4), 640-649, 2007 | 622 | 2007 |
| Efficient optimal learning for contextual bandits M Dudik, D Hsu, S Kale, N Karampatziakis, J Langford, L Reyzin, T Zhang arXiv preprint arXiv:1106.2369, 2011 | 399 | 2011 |
| Loftq: Lora-fine-tuning-aware quantization for large language models Y Li, Y Yu, C Liang, P He, N Karampatziakis, W Chen, T Zhao arXiv preprint arXiv:2310.08659, 2023 | 289 | 2023 |
| Graph-based malware classification based on file relationships JW Stokes, N Karampatziakis, JC Platt, AF Thomas, AM Marinescu US Patent 8,799,190, 2014 | 197 | 2014 |
| Phi-3 technical report: A highly capable language model locally on your phone, 2024 M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... URL https://arxiv. org/abs/2404.14219 2, 6, 2024 | 134 | 2024 |
| Gradient coding R Tandon, Q Lei, AG Dimakis, N Karampatziakis arXiv preprint arXiv:1612.03301, 2016 | 106 | 2016 |
| Online importance weight aware updates N Karampatziakis, J Langford arXiv preprint arXiv:1011.1576, 2010 | 85 | 2010 |
| Anytime-valid off-policy inference for contextual bandits I Waudby-Smith, L Wu, A Ramdas, N Karampatziakis, P Mineiro ACM/IMS Journal of Data Science 1 (3), 1-42, 2024 | 62 | 2024 |
| Logarithmic time one-against-some H Daumé III, N Karampatziakis, J Langford, P Mineiro International Conference on Machine Learning, 923-932, 2017 | 53 | 2017 |
| Using file relationships in malware classification N Karampatziakis, JW Stokes, A Thomas, M Marinescu International Conference on Detection of Intrusions and Malware, and …, 2012 | 47 | 2012 |
| Discriminative features via generalized eigenvectors N Karampatziakis, P Mineiro International conference on machine learning, 494-502, 2014 | 45 | 2014 |
| Least squares revisited: Scalable approaches for multi-class prediction A Agarwal, S Kakade, N Karampatziakis, L Song, G Valiant International Conference on Machine Learning, 541-549, 2014 | 36 | 2014 |
| Parallel online learning D Hsu, N Karampatziakis, J Langford, A Smola arXiv preprint arXiv:1103.4204, 2011 | 35 | 2011 |
| Fast label embeddings via randomized linear algebra P Mineiro, N Karampatziakis Joint European conference on machine learning and knowledge discovery in …, 2015 | 34 | 2015 |
| Active information acquisition H He, P Mineiro, N Karampatziakis arXiv preprint arXiv:1602.02181, 2016 | 29 | 2016 |
| Static analysis of binary executables using structural SVMs N Karampatziakis Advances in Neural Information Processing Systems 23, 2010 | 27 | 2010 |
| Meet in the middle: A new pre-training paradigm A Nguyen, N Karampatziakis, W Chen Advances in Neural Information Processing Systems 36, 5079-5091, 2023 | 21 | 2023 |
Paul MineiroMicrosoftVerified email at mineiro.com
