Learning to Parse Wireframes in Images of Man-Made Environments K Huang, Y Wang, Z Zhou, T Ding, S Gao, Y Ma the IEEE Conference on Computer Vision and Pattern Recognition, 626-635, 2018 | 190 | 2018 |
Noisy Dual Principal Component Pursuit T Ding, Z Zhu, T Ding, Y Yang, R Vidal, M Tsakiris, D Robinson International Conference on Machine Learning, 1617-1625, 2019 | 25 | 2019 |
Robust Homography Estimation via Dual Principal Component Pursuit T Ding, Y Yang, Z Zhu, DP Robinson, R Vidal, L Kneip, MC Tsakiris the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 6080-6089, 2020 | 21 | 2020 |
Efficient Maximal Coding Rate Reduction by Variational Forms C Baek, Z Wu, KHR Chan, T Ding, Y Ma, BD Haeffele the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 500-508, 2022 | 9 | 2022 |
Unsupervised Manifold Linearizing and Clustering T Ding, S Tong, KHR Chan, X Dai, Y Ma, BD Haeffele the IEEE/CVF International Conference on Computer Vision (ICCV), 2023 | 7 | 2023 |
Understanding Doubly Stochastic Clustering T Ding, D Lim, R Vidal, BD Haeffele International Conference on Machine Learning, 5153-5165, 2022 | 6 | 2022 |
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models T Chu, S Tong, T Ding, X Dai, BD Haeffele, R Vidal, Y Ma International Conference on Learning Representations, 2024 | 4 | 2024 |
PaCE: Parsimonious Concept Engineering for Large Language Models J Luo, T Ding, KHR Chan, D Thaker, A Chattopadhyay, C Callison-Burch, ... arXiv preprint arXiv:2406.04331, 2024 | | 2024 |
HARD: Hyperplane ARrangement Descent T Ding, L Peng, R Vidal Conference on Parsimony and Learning, 134-158, 2024 | | 2024 |
Outlier-Robust Orthogonal Regression on Manifolds T Ding, L Peng, R Vidal | | 2023 |
Boosting RANSAC via Dual Principal Component Pursuit Y Yang, X Zhang, T Ding, DP Robinson, R Vidal, MC Tsakiris arXiv preprint arXiv:2110.02918, 2021 | | 2021 |