[ADH+19b] Sanjeev Arora, Simon S Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, and Ruosong Wang. On exact computation with an infinitely wide neural net. In NeurIPS, 2019.
[AEM92] Pankaj K Agarwal, David Eppstein, and Jiri Matousek. Dynamic half-space reporting, geometric optimization, and minimum spanning trees. In Annual Symposium on Foundations of Computer Science (FOCS), volume 33, pages 80-80, 1992.
$\left[\mathrm{AIL}^{+}15\right]$  Alexandr Andoni, Piotr Indyk, TMM Laarhoven, Ilya Razenshteyn, and Ludwig Schmidt. Practical and optimal lsh for angular distance. In Advances in Neural Information Processing Systems (NIPS), pages 1225-1233. Curran Associates, 2015.
[AIR18] Alexandr Andoni, Piotr Indyk, and Ilya Razenshteyn. Approximate nearest neighbor search in high dimensions. arXiv preprint arXiv:1806.09823, 7, 2018.
[AR15] Alexandr Andoni and Ilya Razenshteyn. Optimal data-dependent hashing for approximate near neighbors. In Proceedings of the forty-seventh annual ACM symposium on Theory of computing (STOC), pages 793-801, 2015.
[ARN17] Alexandr Andoni, Ilya Razenshteyn, and Negev Shekel Nosatzki. Lsh forest: Practical algorithms made theoretical. In Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 67-78. SIAM, 2017.
[AS23a] Josh Alman and Zhao Song. Fast attention requires bounded entries. In NeurIPS. arXiv preprint arXiv:2302.13214, 2023.
[AS23b] Josh Alman and Zhao Song. How to capture higher-order correlations? generalizing matrix softmax attention to kronecker computation. arXiv preprint arXiv:2310.04064, 2023.
[AWW14] Amir Abboud, Virginia Vassilevska Williams, and Oren Weimann. Consequences of faster alignment of sequences. In International Colloquium on Automata, Languages, and Programming, pages 39-51. Springer, 2014.
[AWY14] Amir Abboud, Ryan Williams, and Huacheng Yu. More applications of the polynomial method to algorithm design. In Proceedings of the twenty-sixth annual ACM-SIAM symposium on Discrete algorithms, pages 218-230. SIAM, 2014.
[AZLS19a] Zeyuan Allen-Zhu, Yanzhi Li, and Zhao Song. A convergence theory for deep learning via over-parameterization. In ICML, 2019.
[AZLS19b] Zeyuan Allen-Zhu, Yuanzhi Li, and Zhao Song. On the convergence rate of training recurrent neural networks. In NeurIPS, 2019.
$\left[\mathrm{BBK}^{+}16\right]$  Kevin Buchin, Maike Buchin, Maximilian Konzack, Wolfgang Mulzer, and André Schulz. Fine-grained analysis of problems on curves. EuroCG, Lugano, Switzerland, 2016.
[Ber24] Sergei Bernstein. On a modification of chebyshev's inequality and of the error formula of laplace. Ann. Sci. Inst. Sav. Ukraine, Sect. Math, 1(4):38-49, 1924.
[BGL17] Karl Bringmann, Allan Grønlund, and Kasper Green Larsen. A dichotomy for regular expression membership testing. In 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), pages 307–318. IEEE, 2017.
[B115] Arturs Backurs and Piotr Indyk. Edit distance cannot be computed in strongly subquadratic time (unless seth is false). In Proceedings of the forty-seventh annual ACM symposium on Theory of computing, pages 51-58, 2015.
[B116] Arturs Backurs and Piotr Indyk. Which regular expression patterns are hard to match? In 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS), pages 457-466. IEEE, 2016.
[BIW19] Arturs Backurs, Piotr Indyk, and Tal Wagner. Space and time efficient kernel density estimation in high dimensions. In NeurIPS, pages 15773-15782, 2019.