Tianjiao Ding

@article{balzano2025overview,
  title = {An Overview of Low-Rank Structures in the Training and Adaptation of Large Models},
  author = {Balzano, Laura and Ding, Tianjiao and Haeffele, Benjamin D. and Kwon, Soo Min and Qu, Qing and Wang, Peng and Wang, Zhangyang and Yaras, Can},
  journal = {To appear in IEEE Signal Processing Magazine},
  year = {2026},
  note = {Invited paper for Special Issue on Mathematics of Deep Learning},
  tags = {foundation-models;representation-learning;optimization;theory}
}

@inproceedings{luo2025concept,
  title = {Concept Lancet: Image Editing with Compositional Representation Transplant},
  author = {Luo, Jinqi and Ding, Tianjiao and Chan, Kwan Ho Ryan and Min, Hancheng and Callison-Burch, Chris and Vidal, Ren{\'e}},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2025},
  tags = {trustworthy-ml;foundation-models;representation-learning}
}

@inproceedings{wu2025token,
  title = {Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction},
  author = {Wu, Ziyang and Ding, Tianjiao and Lu, Yifu and Pai, Druv and Zhang, Jingyuan and Wang, Weida and Yu, Yaodong and Ma, Yi and Haeffele, Benjamin D.},
  booktitle = {International Conference on Learning Representations},
  year = {2025},
  tags = {efficient-ml;optimization;foundation-models;theory}
}

@inproceedings{luo2024pace,
  title = {PaCE: Parsimonious Concept Engineering for Large Language Models},
  author = {Luo, Jinqi and Ding, Tianjiao and Chan, Kwan Ho Ryan and Thaker, Darshan and Chattopadhyay, Aditya and Callison-Burch, Chris and Vidal, Ren{\'e}},
  booktitle = {Annual Conference on Neural Information Processing Systems},
  year = {2024},
  tags = {trustworthy-ml;efficient-ml;foundation-models;representation-learning}
}

@inproceedings{shinde2024geometric,
  title = {Geometric Analysis of Nonlinear Manifold Clustering},
  author = {Shinde, Nimita and Ding, Tianjiao and Robinson, Daniel P. and Vidal, Ren{\'e}},
  booktitle = {Annual Conference on Neural Information Processing Systems},
  year = {2024},
  tags = {unsupervised-ml;theory;optimization}
}

@inproceedings{chu2024image,
  title = {Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models},
  author = {Chu, Tianzhe and Tong, Shengbang and Ding, Tianjiao and Dai, Xili and Haeffele, Benjamin D. and Vidal, Ren{\'e} and Ma, Yi},
  booktitle = {International Conference on Learning Representations},
  year = {2024},
  tags = {unsupervised-ml;foundation-models;representation-learning}
}

@inproceedings{ding2024hard,
  title = {HARD: Hyperplane ARrangement Descent},
  author = {Ding, Tianjiao and Peng, Liangzu and Vidal, Ren{\'e}},
  booktitle = {Conference on Parsimony and Learning},
  year = {2024},
  tags = {trustworthy-ml;unsupervised-ml;theory;optimization}
}

@inproceedings{ding2023outlier,
  title = {Outlier-Robust Orthogonal Regression on Manifolds},
  author = {Ding, Tianjiao and Peng, Liangzu and Vidal, Ren{\'e}},
  booktitle = {OpenReview},
  year = {2023},
  tags = {trustworthy-ml;efficient-ml;unsupervised-ml;theory;geometric-vision;optimization}
}

@inproceedings{ding2023unsupervised,
  title = {Unsupervised Manifold Linearizing and Clustering},
  author = {Ding, Tianjiao and Tong, Shengbang and Chan, Kwan Ho Ryan and Dai, Xili and Ma, Yi and Haeffele, Benjamin D.},
  booktitle = {International Conference on Computer Vision},
  year = {2023},
  tags = {unsupervised-ml;representation-learning}
}

@inproceedings{ding2022understanding,
  title = {Understanding Doubly Stochastic Clustering},
  author = {Ding, Tianjiao and Lim, Derek and Vidal, Ren{\'e} and Haeffele, Benjamin D.},
  booktitle = {International Conference on Machine Learning},
  year = {2022},
  tags = {unsupervised-ml;trustworthy-ml;optimization;theory}
}

@inproceedings{baek2022efficient,
  title = {Efficient Maximal Coding Rate Reduction by Variational Forms},
  author = {Baek, Christina and Wu, Ziyang and Chan, Kwan Ho Ryan and Ding, Tianjiao and Ma, Yi and Haeffele, Benjamin D.},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2022},
  tags = {efficient-ml;optimization;theory;representation-learning}
}

@article{yang2021boosting,
  title = {Boosting RANSAC via Dual Principal Component Pursuit},
  author = {Yang, Yunchen and Zhang, Xinyue and Ding, Tianjiao and Robinson, Daniel P. and Vidal, Ren{\'e} and Tsakiris, Manolis C.},
  journal = {arXiv preprint arXiv:2110.02918},
  year = {2021},
  tags = {trustworthy-ml;efficient-ml;geometric-vision}
}

@inproceedings{ding2020robust,
  title = {Robust Homography Estimation via Dual Principal Component Pursuit},
  author = {Ding, Tianjiao and Yang, Yunchen and Zhu, Zhihui and Robinson, Daniel P. and Vidal, Ren{\'e} and Kneip, Laurent and Tsakiris, Manolis C.},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
  pages = {6080--6089},
  year = {2020},
  tags = {trustworthy-ml;efficient-ml;unsupervised-ml;geometric-vision;theory;optimization}
}

@inproceedings{ding2019noisy,
  title = {Noisy Dual Principal Component Pursuit},
  author = {Ding, Tianyu and Zhu, Zhihui and Ding, Tianjiao and Yang, Yunchen and Robinson, Daniel P. and Tsakiris, Manolis C. and Vidal, Ren{\'e}},
  booktitle = {International Conference on Machine Learning},
  pages = {1617--1625},
  year = {2019},
  tags = {unsupervised-ml;efficient-ml;trustworthy-ml;geometric-vision;optimization;theory}
}

@inproceedings{huang2018learning,
  title = {Learning to Parse Wireframes in Images of Man-Made Environments},
  author = {Huang, Kun and Wang, Yifan and Zhou, Zihan and Ding, Tianjiao and Gao, Shenghua and Ma, Yi},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
  pages = {626--635},
  year = {2018},
  tags = {efficient-ml;geometric-vision;representation-learning}
}