Projects per year
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Dive into the research topics where Shuzhong Zhang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Data Analytics for High Throughput Drug Screens
Foo, J. Y., Leder, K. Z. & Zhang, S.
6/1/23 → 5/31/26
Project: Research project
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EAGER: New Approach: Early diagnosis of Alzheimers di
ARKANSAS STATE UNIVERSITY, THE NATIONAL SCIENCE FOUNDATION
8/1/17 → 6/30/19
Project: Research project
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SCH: EAGER: New Approach: Early Diagnosis of Alzheimer's Disease Based on Magnetic Resonance Imaging (MRI) via High-Dimensional Image Feature Identification
Huang, X. & Zhang, S.
8/1/17 → 7/31/22
Project: Research project
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First Order Methods for Solving Tensor Projection and Co
THE NATIONAL SCIENCE FOUNDATION
9/1/15 → 8/31/19
Project: Research project
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Gradient Methods for Solving Big Data (Tensor) Optimization Problems
9/1/15 → 8/31/19
Project: Research project
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Linearly-Convergent FISTA Variant for Composite Optimization with Duality
Garner, C. & Zhang, S., Mar 2023, In: Journal of Scientific Computing. 94, 3, 65.Research output: Contribution to journal › Article › peer-review
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MINIMAX PROBLEMS WITH COUPLED LINEAR CONSTRAINTS: COMPUTATIONAL COMPLEXITY AND DUALITY
Tsaknakis, I., Hong, M. & Zhang, S., 2023, In: SIAM Journal on Optimization. 33, 4, p. 2675-2702 28 p.Research output: Contribution to journal › Article › peer-review
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Polar Decomposition-based Algorithms on the Product of Stiefel Manifolds with Applications in Tensor Approximation
Li, J. Z. & Zhang, S. Z., 2023, (Accepted/In press) In: Journal of the Operations Research Society of China.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
PRIMAL-DUAL FIRST-ORDER METHODS FOR AFFINELY CONSTRAINED MULTI-BLOCK SADDLE POINT PROBLEMS
Zhang, J., Wang, M., Hong, M. & Zhang, S., 2023, In: SIAM Journal on Optimization. 33, 2, p. 1035-1060 26 p.Research output: Contribution to journal › Article › peer-review
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Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling
Chen, X., Jiang, B., Lin, T. & Zhang, S., 2022, In: Journal of Machine Learning Research. 23Research output: Contribution to journal › Article › peer-review
5 Scopus citations