| Simplifying graph convolutional networks F Wu, T Zhang, AH Souza Jr, C Fifty, T Yu, KQ Weinberger Proceedings of the 36th International Conference on Machine Learning (ICML 2019), 2019 | 3836 | 2019 |
| Salvaging federated learning by local adaptation T Yu, E Bagdasaryan, V Shmatikov arXiv preprint arXiv:2002.04758, 2020 | 323 | 2020 |
| A New Defense Against Adversarial Images: Turning a Weakness into a Strength T Yu, S Hu, C Guo, WL Chao, KQ Weinberger Advances in Neural Information Processing Systems, 2019 | 145 | 2019 |
| Numerically accurate hyperbolic embeddings using tiling-based models T Yu, CM De Sa Advances in Neural Information Processing Systems 32, 2019 | 48 | 2019 |
| Understanding hyperdimensional computing for parallel single-pass learning T Yu, Y Zhang, Z Zhang, CM De Sa Advances in neural information processing systems 35, 1157-1169, 2022 | 31 | 2022 |
| Simplifying graph convolutional networks. arXiv 2019 F Wu, T Zhang, AHD Souza Jr, C Fifty, T Yu, KQ Weinberger arXiv preprint arXiv:1902.07153, 1902 | 17 | 1902 |
| Random Laplacian Features for Learning with Hyperbolic Space T Yu, C De Sa Eleventh International Conference on Learning Representations (ICLR 2023), 2022 | 14* | 2022 |
| Curvature-based Comparison of Two Neural Networks T Yu, H Long, J Hopcroft Proceedings of the 24th International Conference on Pattern Recognition …, 2018 | 14 | 2018 |
| Representing hyperbolic space accurately using multi-component floats T Yu, CM De Sa Advances in Neural Information Processing Systems 34, 15570-15581, 2021 | 13 | 2021 |
| Coneheads: hierarchy aware attention A Tseng, T Yu, T Liu, CM De Sa Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| Shadow Cones: Unveiling Partial Orders in Hyperbolic Space T Yu, TJB Liu, A Tseng, C De Sa Twelfth International Conference on Learning Representations (ICLR 2024), 2023 | 4 | 2023 |
| Mctensor: A high-precision deep learning library with multi-component floating-point T Yu, W Guo, JC Li, T Yuan, C De Sa arXiv preprint arXiv:2207.08867, 2022 | 4 | 2022 |
| The Local Dimension of Deep Manifold M Zhang, W Wu, Y Zhang, K He, T Yu, H Long, JE Hopcroft arXiv preprint arXiv:1711.01573, 2017 | 3 | 2017 |
| Collage: Light-Weight Low-Precision Strategy for LLM Training T Yu, G Gupta, K Gopalswamy, A Mamidala, H Zhou, J Huynh, Y Park, ... arXiv preprint arXiv:2405.03637, 2024 | 1 | 2024 |
| Momentum Approximation in Asynchronous Private Federated Learning T Yu, C Song, J Wang, M Chitnis arXiv preprint arXiv:2402.09247, 2024 | 1 | 2024 |
| Knowledge-based Fully Convolutional Network and Its Application in Segmentation of Lung CT Images T Yu, Y Qiao, L Huan arXiv preprint arXiv:1805.08492, 2018 | 1 | 2018 |
| Simplifying Graph Convolutional Networks (Supplementary Material) F Wu, T Zhang, AH de Souza Jr, C Fifty, T Yu, KQ Weinberger Proceedings of the 36th International Conference on Machine Learning (ICML 2019), 0 | 1 | |
| Towards Expressive and Robust Learning With Hyperbolic Geometry T Yu Cornell University, 2024 | | 2024 |
Kilian WeinbergerCornell UniversityПодтвержден адрес электронной почты в домене cornell.edu
