Methods for quantized compressed sensing. - Hao-Jun Michael Shi; Mindy Case; Xiaoyi Gu; Shenyinying Tu; Deanna Needell (ITA, 2016)

Practical Algorithms for Learning Near-Isometric Linear Embeddings. - Jerry Luo; Kayla Shapiro; Hao-Jun Michael Shi; Qi Yang; Kan Zhu (CoRR, 2016)

A Progressive Batching L-BFGS Method for Machine Learning. - Raghu Bollapragada; Dheevatsa Mudigere; Jorge Nocedal; Hao-Jun Michael Shi; Ping Tak Peter Tang (ICML, 2018)

Optimizing Quantization for Lasso Recovery. - Xiaoyi Gu; Shenyinying Tu; Hao-Jun Michael Shi; Mindy Case; Deanna Needell; Yaniv Plan (IEEE Signal Process. Lett., 2018)

Deep Learning Recommendation Model for Personalization and Recommendation Systems. - Maxim Naumov; Dheevatsa Mudigere; Hao-Jun Michael Shi; Jianyu Huang; Narayanan Sundaraman; Jongsoo Park; Xiaodong Wang 020; Udit Gupta; Carole-Jean Wu; Alisson G. Azzolini; Dmytro Dzhulgakov; Andrey Mallevich; et al. (CoRR, 2019)

Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems. - Hao-Jun Michael Shi; Dheevatsa Mudigere; Maxim Naumov; Jiyan Yang (KDD, 2020)

A Noise-Tolerant Quasi-Newton Algorithm for Unconstrained Optimization. - Hao-Jun Michael Shi; Yuchen Xie; Richard H. Byrd; Jorge Nocedal (SIAM J. Optim., 2022)

Adaptive Finite-Difference Interval Estimation for Noisy Derivative-Free Optimization. - Hao-Jun Michael Shi; Yuchen Xie; Melody Qiming Xuan; Jorge Nocedal (SIAM J. Sci. Comput., 2022)

A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale. - Hao-Jun Michael Shi; Tsung-Hsien Lee; Shintaro Iwasaki; Jose Gallego-Posada; Zhijing Li 001; Kaushik Rangadurai; Dheevatsa Mudigere; Michael Rabbat (CoRR, 2023)

On the numerical performance of finite-difference-based methods for derivative-free optimization. - Hao-Jun Michael Shi; Melody Qiming Xuan; Figen Öztoprak; Jorge Nocedal (Optim. Methods Softw., 2023)

Purifying Shampoo: Investigating Shampoo's Heuristics by Decomposing its Preconditioner. - Runa Eschenhagen; Aaron Defazio; Tsung-Hsien Lee; Richard E. Turner; Hao-Jun Michael Shi (CoRR, 2025)