| Pixmatch: Unsupervised domain adaptation via pixelwise consistency training L Melas-Kyriazi, AK Manrai Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 51 | 2021 |
| Do you even need attention? a stack of feed-forward layers does surprisingly well on imagenet L Melas-Kyriazi arXiv preprint arXiv:2105.02723, 2021 | 50 | 2021 |
| Training for diversity in image paragraph captioning L Melas-Kyriazi, AM Rush, G Han proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 48 | 2018 |
| Show, edit and tell: a framework for editing image captions F Sammani, L Melas-Kyriazi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 43 | 2020 |
| Encoder-agnostic adaptation for conditional language generation ZM Ziegler, L Melas-Kyriazi, S Gehrmann, AM Rush arXiv preprint arXiv:1908.06938, 2019 | 43 | 2019 |
| Finding an unsupervised image segmenter in each of your deep generative models L Melas-Kyriazi, C Rupprecht, I Laina, A Vedaldi International Conference on Learning Representations, 2022 | 23 | 2022 |
| Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization L Melas-Kyriazi, C Rupprecht, I Laina, A Vedaldi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 20 | 2022 |
| Prediction of chronological and biological age from laboratory data L Sagers, L Melas-Kyriazi, CJ Patel, AK Manrai Aging (Albany NY) 12 (9), 7626, 2020 | 19 | 2020 |
| The mathematical foundations of manifold learning L Melas-Kyriazi arXiv preprint arXiv:2011.01307, 2020 | 14 | 2020 |
| Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings L Melas-Kyriazi, G Han, C Liang EMNLP 2019 Workshop on Deep Learning for Low-resource NLP, 2020 | 7 | 2020 |
| Prompt-and-rerank: A method for zero-shot and few-shot arbitrary textual style transfer with small language models M Suzgun, L Melas-Kyriazi, D Jurafsky arXiv preprint arXiv:2205.11503, 2022 | 4 | 2022 |
| Follow the wisdom of the crowd: Effective text generation via minimum bayes risk decoding M Suzgun, L Melas-Kyriazi, D Jurafsky arXiv preprint arXiv:2211.07634, 2022 | 2 | 2022 |
| The Geometry of Semi-Supervised Learning L Melas-Kyriazi PhD thesis, 2020 | 2 | 2020 |
| The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications M Suzgun, L Melas-Kyriazi, SK Sarkar, SD Kominers, SM Shieber arXiv preprint arXiv:2207.04043, 2022 | 1 | 2022 |
| Intrinsic Gradient Compression for Scalable and Efficient Federated Learning L Melas-Kyriazi, F Wang Proceedings of the First Workshop on Federated Learning for Natural Language …, 2022 | 1 | 2022 |
| Intrinisic Gradient Compression for Federated Learning L Melas-Kyriazi, F Wang arXiv preprint arXiv:2112.02656, 2021 | | 2021 |
Alexander M. RushAssociate Professor, Cornell UniversityVerified email at seas.harvard.edu
