[CW16] Timothy M Chan and Ryan Williams. Deterministic apsp, orthogonal vectors, and more: Quickly derandomizing razborov-smolensky. In Proceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete algorithms, pages 1246-1255. SIAM, 2016.
[CW19] Lijie Chen and Ryan Williams. An equivalence class for orthogonal vectors. In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 21-40. SIAM, 2019.
[CWX22] Timothy M Chan, Virginia Vassilevska Williams, and Yinzhan Xu. Hardness for triangle problems under even more believable hypotheses: Reductions from real apsp, real 3sum, and ov. arXiv preprint arXiv:2203.08356, 2022.
$\left[\mathrm{DCL}^{+}22\right]$  Tri Dao, Beidi Chen, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, and Christopher Re. Pixelated butterfly: Simple and efficient sparse training for neural network models. In ICLR. arXiv preprint arXiv:2112.00029, 2022.
[DIIM04] Mayur Datar, Nicole Immorlica, Piotr Indyk, and Vahab S Mirrokni. Locality-sensitive hashing scheme based on p-stable distributions. In Proceedings of the twentieth annual symposium on Computational geometry (SoCG), pages 253-262, 2004.
[DIRW20] Yihe Dong, Piotr Indyk, Ilya Razenshteyn, and Tal Wagner. Learning space partitions for nearest neighbor search. In *ICLR*. arXiv preprint arXiv:1901.08544, 2020.
[DLW22] Mina Dalirrooyfard, Ray Li, and Virginia Vassilevska Williams. Hardness of approximate diameter: Now for undirected graphs. In 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS), pages 1021-1032. IEEE, 2022.
[DMS23] Yichuan Deng, Sridhar Mahadevan, and Zhao Song. Randomized and deterministic attention sparsification algorithms for over-parameterized feature dimension. arXiv preprint arXiv:2304.04397, 2023.
[DSZ23] Yichuan Deng, Zhao Song, and Tianyi Zhou. Superiority of softmax: Unveiling the performance edge over linear attention. arXiv preprint arXiv:2310.11685, 2023.
[DZPS19] Simon S Du, Xiyu Zhai, Barnabas Poczos, and Aarti Singh. Gradient descent provably optimizes over-parameterized neural networks. In ICLR, 2019.
[GIKW18] Jiawei Gao, Russell Impagliazzo, Antonina Kolokolova, and Ryan Williams. Completeness for first-order properties on sparse structures with algorithmic applications. ACM Transactions on Algorithms (TALG), 15(2):1-35, 2018.
[GMS23] Yeqi Gao, Sridhar Mahadevan, and Zhao Song. An over-parameterized exponential regression. arXiv preprint arXiv:2303.16504, 2023.
[GS22] Yuzhou Gu and Zhao Song. A faster small treewidth sdp solver. arXiv preprint arXiv:2211.06033, 2022.
[GSY23] Yeqi Gao, Zhao Song, and Junze Yin. Gradientcoin: A peer-to-peer decentralized large language models. arXiv preprint arXiv:2308.10502, 2023.
[GSYZ23] Yeqi Gao, Zhao Song, Xin Yang, and Ruizhe Zhang. Fast quantum algorithm for attention computation. arXiv preprint arXiv:2307.08045, 2023.
[GSZ23] Yuzhou Gu, Zhao Song, and Lichen Zhang. A nearly-linear time algorithm for structured support vector machines. arXiv preprint arXiv:2307.07735, 2023.
[HLSY21] Baihe Huang, Xiaoxiao Li, Zhao Song, and Xin Yang. Fl-ntk: A neural tangent kernel-based framework for federated learning convergence analysis. In ICML, 2021.
[HSWZ22] Hang Hu, Zhao Song, Omri Weinstein, and Danyang Zhuo. Training overparametrized neural networks in sublinear time. arXiv preprint arXiv:2208.04508, 2022.