An Algebraic-Geometric Approach to Shuffled Linear Regression. - Manolis C. Tsakiris; Liangzu Peng; Aldo Conca; Laurent Kneip; Yuanming Shi; Hayoung Choi (CoRR, 2018)

Algebraically-initialized Expectation Maximization for Header-free Communication. - Liangzu Peng; Xuming Song; Manolis C. Tsakiris; Hayoung Choi; Laurent Kneip; Yuanming Shi (ICASSP, 2019)

Homomorphic Sensing. - Manolis C. Tsakiris; Liangzu Peng (ICML, 2019)

Homomorphic Sensing of Subspace Arrangements. - Liangzu Peng; Boshi Wang; Manolis C. Tsakiris (CoRR, 2020)

Linear Regression Without Correspondences via Concave Minimization. - Liangzu Peng; Manolis C. Tsakiris (IEEE Signal Process. Lett., 2020)

An Algebraic-Geometric Approach for Linear Regression Without Correspondences. - Manolis C. Tsakiris; Liangzu Peng; Aldo Conca; Laurent Kneip; Yuanming Shi; Hayoung Choi (IEEE Trans. Inf. Theory, 2020)

Homomorphic Sensing: Sparsity and Noise. - Liangzu Peng; Boshi Wang; Manolis C. Tsakiris (ICML, 2021)

Unsigned Matrix Completion. - Yunzhen Yao; Liangzu Peng; Manolis C. Tsakiris (ISIT, 2021)

Unlabeled Principal Component Analysis. - Yunzhen Yao; Liangzu Peng; Manolis C. Tsakiris (NeurIPS, 2021)

ARCS: Accurate Rotation and Correspondence Search. - Liangzu Peng; Manolis C. Tsakiris; René Vidal (CVPR, 2022)

Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or Not. - Liangzu Peng; Mahyar Fazlyab; René Vidal (ECCV (23), 2022)

Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression. - Liangzu Peng; Christian Kümmerle; René Vidal (NeurIPS, 2022)

Towards Understanding The Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search. - Liangzu Peng; Mahyar Fazlyab; René Vidal (CoRR, 2022)

On the Convergence of IRLS and Its Variants in Outlier-Robust Estimation. - Liangzu Peng; Christian Kümmerle; René Vidal (CVPR, 2023)

The Ideal Continual Learner: An Agent That Never Forgets. - Liangzu Peng; Paris Giampouras; René Vidal (ICML, 2023)

HARD: Hyperplane ARrangement Descent. - Tianjiao Ding; Liangzu Peng; René Vidal (CPAL, 2024)

Scalable 3D Registration via Truncated Entry-Wise Absolute Residuals. - Tianyu Huang; Liangzu Peng; René Vidal; Yun-Hui Liu 001 (CVPR, 2024)

Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares. - Liangzu Peng; Wotao Yin (ICML, 2024)

ICL-TSVD: Bridging Theory and Practice in Continual Learning with Pre-trained Models. - Liangzu Peng; Juan Elenter; Joshua Agterberg; Alejandro Ribeiro; René Vidal (CoRR, 2024)

Unlabeled Principal Component Analysis and Matrix Completion. - Yunzhen Yao; Liangzu Peng; Manolis C. Tsakiris (J. Mach. Learn. Res., 2024)

Accelerating Globally Optimal Consensus Maximization in Geometric Vision. - Xinyue Zhang; Liangzu Peng; Wanting Xu; Laurent Kneip (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Efficient and Robust Point Cloud Registration via Heuristics-Guided Parameter Search. - Tianyu Huang; Haoang Li; Liangzu Peng; Yinlong Liu; Yun-Hui Liu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning. - Liangzu Peng; Juan Elenter; Joshua Agterberg; Alejandro Ribeiro; René Vidal (ICLR, 2025)

Mathematics of Continual Learning. - Liangzu Peng; René Vidal (CoRR, 2025)