Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Jiacheng Zhuo (CoRR, 2017)

Bottom-Up Object Detection by Grouping Extreme and Center Points. - Xingyi Zhou; Jiacheng Zhuo; Philipp Krähenbühl (CVPR, 2019)

K-Best Transformation Synchronization. - Yifan Sun 007; Jiacheng Zhuo; Arnav Mohan; Qixing Huang (ICCV, 2019)

Primal-Dual Block Generalized Frank-Wolfe. - Qi Lei; Jiacheng Zhuo; Constantine Caramanis; Inderjit S. Dhillon; Alexandros G. Dimakis (NeurIPS, 2019)

Primal-Dual Block Frank-Wolfe. - Qi Lei; Jiacheng Zhuo; Constantine Caramanis; Inderjit S. Dhillon; Alexandros G. Dimakis (CoRR, 2019)

Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization. - Fanhua Shang; Bingkun Wei; Hongying Liu 001; Yuanyuan Liu 001; Jiacheng Zhuo (CoRR, 2019)

Weaving geodesic foliations. - Josh Vekhter; Jiacheng Zhuo; Luisa F. Gil Fandino; Qixing Huang; Etienne Vouga (ACM Trans. Graph., 2019)

Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. - Jiacheng Zhuo; Qi Lei; Alex Dimakis; Constantine Caramanis (AISTATS, 2020)

Robust Structured Statistical Estimation via Conditional Gradient Type Methods. - Jiacheng Zhuo; Liu Liu; Constantine Caramanis (CoRR, 2020)

Predicting What You Already Know Helps: Provable Self-Supervised Learning. - Jason D. Lee; Qi Lei; Nikunj Saunshi; Jiacheng Zhuo (NeurIPS, 2021)

Improving Computational Complexity in Statistical Models with Second-Order Information. - Tongzheng Ren; Jiacheng Zhuo; Sujay Sanghavi; Nhat Ho (CoRR, 2022)

Improving Computational Complexity in Statistical Models with Local Curvature Information. - Pedram Akbarian; Tongzheng Ren; Jiacheng Zhuo; Sujay Sanghavi; Nhat Ho (ICML, 2024)

On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing. - Jiacheng Zhuo; Jeongyeol Kwon; Nhat Ho; Constantine Caramanis (J. Mach. Learn. Res., 2024)