About Me
I am a fifth year Ph.D candidate studying Computer Science at University of Texas at Austin, advised by Prof. Dana Moshkovitz. My research interests mainly lie in theoretical computer science. Currently I’m working on quantum algorithms, optimization, meta-complexity, and deep learning theory. I am always open to new topics.
Publications
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Hyperbolic Extension of Kadison-Singer Type Results
- Ruizhe Zhang, Xinzhi Zhang
- To appear in the 50th EATCS International Colloquium on Automata, Languages, and Programming (ICALP'2023)
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Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision
- Guoming Wang, Daniel Stilck-França, Ruizhe Zhang, Shuchen Zhu, Peter D. Johnson
- Contributed talk at the third Quantum Computing Theory in Practice (QCTIP'2023)
- [arXiv]
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Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits
- Tongyang Li, Ruizhe Zhang
- In Proceedings of the 36-th Conference on Neural Information Processing Systems (NeurIPS'2022)
- [arXiv] [Conference]
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Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants
- Andrew Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang
- In Proceedings of the 36-th Conference on Neural Information Processing Systems (NeurIPS'2022)
- Contributed talk at the 26-th Conference on Quantum Information Processing (QIP'2023)
- [arXiv] [Conference]
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Fast Distance Oracles for Any Symmetric Norm
- Yichuan Deng, Zhao Song, Omri Weinstein, Ruizhe Zhang
- In Proceedings of the 36-th Conference on Neural Information Processing Systems (NeurIPS'2022)
- [arXiv] [Conference]
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Solving SDP Faster: A Robust IPM Framework and Efficient Implementation
- Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang
- In Proceedings of the 63rd Annual Symposium on Foundations of Computer Science (FOCS 2022)
- [arXiv] [Conference]
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Eigenstripping, Spectral Decay, and Edge-Expansion on Posets
- Jason Gaitonde, Max Hopkins, Tali Kaufman, Shachar Lovett, Ruizhe Zhang
- In Proceedings of the 26th International Conference on Randomization and Computation (RANDOM'2022)
- [arXiv] [Conference]
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Hyperbolic Concentration, Anti-concentration, and
Discrepancy
- Zhao Song, Ruizhe Zhang
- In Proceedings of the 26th International Conference on Randomization and Computation (RANDOM'2022)
- [arXiv] [Conference]
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Computing Ground State Properties with Early Fault-Tolerant Quantum Computers
- Ruizhe Zhang, Guoming Wang, Peter Johnson
- In Quantum, Volume 6, Number 761 (2022)
- [arXiv] [Journal] [Quantum View]
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Quantum Meets Minimum Circuit Size Problem
- Nai-Hui Chia, Chi-Ning Chou, Jiayu Zhang, Ruizhe Zhang
- In Proceedings of the 13th Innovations in Theoretical Computer Science Conference (ITCS'2022)
- [arXiv] [eccc] [Conference]
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Symmetric Sparse Boolean Matrix Factorization and Applications
- Sitan Chen, Zhao Song, Runzhou Tao, Ruizhe Zhang
- In Proceedings of the 13th Innovations in Theoretical Computer Science Conference (ITCS'2022)
- [arXiv] [Conference]
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Does Preprocessing Help Training Over-parameterized Neural Networks?
- Zhao Song, Shuo Yang, Ruizhe Zhang
- In Proceedings of the 35-th Conference on Neural Information Processing Systems (NeurIPS'2021)
- [arXiv] [Conference]
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New Approaches for Quantum Copy-Protection
- Scott Aaronson, Jiahui Liu, Qipeng Liu, Mark Zhandry, Ruizhe Zhang
- In Proceedings of the 41st Annual International Cryptology Conference (Crypto'2021)
- Contributed talk at the 16th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC'2021)
- [arXiv] [Conference]
- QED driven QAOA for network-flow optimization
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On the Quantum Complexity of Closest Pair and Related Problems
- Scott Aaronson, Nai-Hui Chia, Han-Hsuan Lin, Chunhao Wang, Ruizhe Zhang
- In Proceedings of the 35th Computational Complexity Conference (CCC'2020)
- Contributed talk at the 15th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC'2020)
- [arXiv] [Conference]
Manuscripts
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Convergence and Generalization of Wide Neural Networks with Large Bias
- Hongru Yang, Ziyu Jiang, Ruizhe Zhang, Zhangyang Wang, Yingbin Liang
- [arXiv]
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Bypass exponential time preprocessing: Fast neural network training via weight-data correlation preprocessing
- Josh Alman, Jiehao Liang, Zhao Song, Ruizhe Zhang, Danyang Zhuo
- [arXiv]
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Quartic Samples Suffice for Fourier Interpolation
- Zhao Song, Baocheng Sun, Omri Weinstein, Ruizhe Zhang
- [arXiv]
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Sparse Fourier Transform over Lattices: A Unified Approach to Signal Reconstruction
- Zhao Song, Baocheng Sun, Omri Weinstein, Ruizhe Zhang
- [arXiv]
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A Dynamic Fast Gaussian Transform
- Baihe Huang, Zhao Song, Omri Weinstein, Hengjie Zhang, Ruizhe Zhang
- [arXiv]
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Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time
- Zhao Song, Lichen Zhang, Ruizhe Zhang
- [arXiv]
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InstaHide's Sample Complexity When Mixing Two Private Images
- Baihe Huang, Zhao Song, Runzhou Tao, Ruizhe Zhang, Danyang Zhuo
- [arXiv]