| Structured Logconcave Sampling with a Restricted Gaussian Oracle YT Lee, R Shen, K Tian Conference on Learning Theory, 2021, 2020 | 114 | 2020 |
| Variance Reduction for Matrix Games Y Carmon, Y Jin, A Sidford, K Tian Advances in Neural Information Processing Systems, 2019, 2019 | 104 | 2019 |
| A Direct O~(1/ε) Iteration Parallel Algorithm for Optimal Transport A Jambulapati, A Sidford, K Tian Advances in Neural Information Processing Systems, 2019, 2019 | 79 | 2019 |
| Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration MB Cohen, A Sidford, K Tian Innovations in Theoretical Computer Science (ITCS), 2021, 2021 | 69 | 2021 |
| Acceleration with a Ball Optimization Oracle Y Carmon, A Jambulapati, Q Jiang, Y Jin, YT Lee, A Sidford, K Tian Advances in Neural Information Processing Systems, 2020, 2020 | 67 | 2020 |
| Predicting gene expression in massively parallel reporter assays: A comparative study A Kreimer, H Zeng, MD Edwards, Y Guo, K Tian, S Shin, R Welch, ... Human mutation 38 (9), 1240-1250, 2017 | 60 | 2017 |
| Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo YT Lee, R Shen, K Tian Conference on Learning Theory, 2020, 2020 | 59 | 2020 |
| A novel k-mer set memory (KSM) motif representation improves regulatory variant prediction Y Guo, K Tian, H Zeng, X Guo, DK Gifford Genome research 28 (6), 891-900, 2018 | 58 | 2018 |
| CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods Genome biology 25 (1), 53, 2024 | 56 | 2024 |
| Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing A Jambulapati, J Li, K Tian Advances in Neural Information Processing Systems, 2020, 2020 | 56 | 2020 |
| Sharper rates for separable minimax and finite sum optimization via primal-dual extragradient methods Y Jin, A Sidford, K Tian Conference on Learning Theory, 4362-4415, 2022 | 52 | 2022 |
| Learning populations of parameters K Tian, W Kong, G Valiant Advances in Neural Information Processing Systems, 2017, 2017 | 52 | 2017 |
| Coordinate Methods for Accelerating Regression and Faster Approximate Maximum Flow A Sidford, K Tian Foundations of Computer Science (FOCS), 2018 IEEE 59th Annual Symposium on, 2018 | 49* | 2018 |
| Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space∗ S Assadi, A Jambulapati, Y Jin, A Sidford, K Tian Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 47 | 2022 |
| Coordinate Methods for Matrix Games Y Carmon, Y Jin, A Sidford, K Tian Foundations of Computer Science (FOCS), 2020, 2020 | 47 | 2020 |
| On the power dominating sets of hypercubes N Dean, A Ilic, I Ramirez, J Shen, K Tian 2011 14th IEEE international conference on computational science and …, 2011 | 40 | 2011 |
| Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions YT Lee, R Shen, K Tian Advances in Neural Information Processing Systems, 2021, 2021 | 39 | 2021 |
| A CS guide to the quantum singular value transformation E Tang, K Tian 2024 Symposium on Simplicity in Algorithms (SOSA), 121-143, 2024 | 36 | 2024 |
| A Rank-1 Sketch for Matrix Multiplicative Weights Y Carmon, JC Duchi, A Sidford, K Tian Conference on Learning Theory, 2019, 2019 | 36 | 2019 |
| Clustering mixture models in almost-linear time via list-decodable mean estimation I Diakonikolas, DM Kane, D Kongsgaard, J Li, K Tian Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 31 | 2022 |
Aaron SidfordStanford UniversityVerified email at stanford.edu
