Bumsu Kim, Daniel Mckenzie,
HQ Cai, and Wotao Yin. Curvature-Aware Derivative-Free Optimization, submitted.
Journal and Selected Conference Papers
HQ Cai, Zehan Chao, Longxiu Huang, and Deanna Needell. Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption, SIAM Journal on Imaging Sciences (SIIMS), to appear.
Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, and
HQ Cai. Towards Constituting Mathematical Structures for Learning to Optimize, In International Conference on Machine Learning (ICML), 2023.
HQ Cai, Longxiu Huang, Pengyu Li, and Deanna Needell. Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(8): 10100–10113, 2023.
HQ Cai, Jian-Feng Cai, and Juntao You. Structured Gradient Descent for Fast Robust Low-Rank Hankel Matrix Completion, SIAM Journal on Scientific Computing (SISC), 45(3): A1172-A1198, 2023.
HQ Cai, Daniel Mckenzie, Wotao Yin, and Zhenliang Zhang. A One-Bit, Comparison-Based Gradient Estimator, Applied and Computational Harmonic Analysis (ACHA), 60: 242–266, 2022.
HQ Cai, Daniel Mckenzie, Wotao Yin, and Zhenliang Zhang. Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling, SIAM Journal on Optimization (SIOPT), 32(2): 687–714, 2022.
HQ Cai, Jialin Liu, and Wotao Yin. Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. In Advances in Neural Information Processing Systems (NeruIPS), 2021.
HQ Cai, Yuchen Lou, Daniel Mckenzie, and Wotao Yin. A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization. In International Conference on Machine Learning (ICML), 2021.
HQ Cai, Keaton Hamm, Longxiu Huang, and Deanna Needell. Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions. Journal of Machine Learning Research (JMLR), 22(185): 1–36, 2021.
HQ Cai, Keaton Hamm, Longxiu Huang, and Deanna Needell. Robust CUR Decomposition: Theory and Imaging Applications. SIAM Journal on Imaging Sciences (SIIMS), 14(4): 1472–1503, 2021.
HQ Cai, Keaton Hamm, Longxiu Huang, Jiaqi Li, and Tao Wang. Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation. IEEE Signal Processing Letters (SPL), 28: 116–120, 2021.
HQ Cai, Jian-Feng Cai, Tianming Wang, and Guojian Yin. Accelerated Structured Alternating Projections for Robust Spectrally Sparse Signal Recovery. IEEE Transactions on Signal Processing (TSP), 69: 809–821, 2021.
HQ Cai, Jian-Feng Cai, and Ke Wei. Accelerated Alternating Projections for Robust Principal Component Analysis. Journal of Machine Learning Research (JMLR), 20(1): 685–717, 2019.
Other Referred Conference and Workshop Papers
Chandler Smith, Samuel Lichtenberg,
HQ Cai, and Abiy Tasissa. Riemannian Optimization for Euclidean Distance Geometry. In Conference on Neural Information Processing Systems (NeruIPS) Workshops, 2023.
Zheng Tan, Longxiu Huang,
HQ Cai, and Yifei Lou. Non-convex Approaches for Low-Rank Tensor Completion under Tubal Sampling. In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
Keaton Hamm, Mohamed Meskini, and
HQ Cai. Riemannian CUR Decompositions for Robust Principal Component Analysis. In International Conference on Machine Learning (ICML) Workshops, 2022.
HQ Cai, Zehan Chao, Longxiu Huang, and Deanna Needell. Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition. In International Conference on Computer Vision (ICCV) Workshops, 2021.
Dylan King, Caroline Hills, Michael Kielstra, and Matt Torrence.
Parallel Time Integration for Constrained Optimization. Lawrence Livermore National Lab, Report No. LLNL-SR-822456, 2020. Academic Mentor: HQ Cai. Sponsoring Mentors: Rob Falgout, Jeff Hittinger, and Cosmin Petra.
Elijah Gross-Sable, Jacky Lee, Xia Li, Tyler Sam, and Nate Sands.
Trained to Kill: Analyzing Homicide Data in Los Angeles County. UCLA Computational and Applied Mathematics REU, Final Report for LA Homicide Narratives, 2019. Principal Investigators: Andrea Bertozzi and Jeffrey Brantingham. Academic Mentors: Michael Lindstrom and HQ Cai.