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Tianjiao Ding
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Cited by
Year
Learning to Parse Wireframes in Images of Man-Made Environments
K Huang, Y Wang, Z Zhou, T Ding, S Gao, Y Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
2132018
Noisy Dual Principal Component Pursuit
T Ding*, Z Zhu*, T Ding, Y Yang, R Vidal, MC Tsakiris, DP Robinson
International Conference on Machine Learning (ICML), 2019
242019
Robust Homography Estimation via Dual Principal Component Pursuit
T Ding, Y Yang, Z Zhu, DP Robinson, R Vidal, L Kneip, MC Tsakiris
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
212020
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 (ICLR), 2024
102024
Efficient Maximal Coding Rate Reduction by Variational Forms
C Baek*, Z Wu*, KHR Chan, T Ding, Y Ma, BD Haeffele
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
102022
Understanding Doubly Stochastic Clustering
T Ding, D Lim, R Vidal, BD Haeffele
International Conference on Machine Learning (ICML), 2022
92022
Unsupervised Manifold Linearizing and Clustering
T Ding, S Tong, KHR Chan, X Dai, Y Ma, BD Haeffele
IEEE International Conference on Computer Vision (ICCV), 2023
82023
PaCE: Parsimonious Concept Engineering for Large Language Models
J Luo*, T Ding*, KHR Chan, D Thaker, A Chattopadhyay, ...
arXiv preprint arXiv:2406.04331, 2024
32024
HARD: Hyperplane ARrangement Descent
T Ding*, L Peng*, R Vidal
Conference on Parsimony and Learning (CPAL), 2024
2024
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
Geometric Analysis of Nonlinear Manifold Clustering
N Shinde, T Ding, D Robinson, R Vidal
The Thirty-eighth Annual Conference on Neural Information Processing Systems, 0
Outlier-Robust Orthogonal Regression on Manifolds
T Ding, L Peng, R Vidal
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Articles 1–12