Tian, Kevin

28 publications

NeurIPS 2025 More of the Same: Persistent Representational Harms Under Increased Representation Jennifer Mickel, Maria De-Arteaga, Liu Leqi, Kevin Tian
NeurIPS 2025 Private Geometric Median in Nearly-Linear Time Syamantak Kumar, Daogao Liu, Kevin Tian, Chutong Yang
COLT 2025 Spike-and-Slab Posterior Sampling in High Dimensions Symantak Kumar, Purnamrita Sarkar, Kevin Tian, Yusong Zhu
NeurIPS 2025 The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination Adam Klivans, Konstantinos Stavropoulos, Kevin Tian, Arsen Vasilyan
COLT 2024 Black-Box K-to-1-PCA Reductions: Theory and Applications Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
COLT 2024 Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization Arun Jambulapati, Aaron Sidford, Kevin Tian
NeurIPS 2024 Learning Noisy Halfspaces with a Margin: Massart Is No Harder than Random Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian
NeurIPS 2024 Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions Hilal Asi, Daogao Liu, Kevin Tian
NeurIPS 2024 Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
NeurIPS 2024 Testing Calibration in Nearly-Linear Time Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang
COLT 2023 Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
ICML 2023 Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling Adam Bouland, Yosheb M Getachew, Yujia Jin, Aaron Sidford, Kevin Tian
NeurIPS 2023 Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations Arun Jambulapati, Kevin Tian
COLT 2023 Semi-Random Sparse Recovery in Nearly-Linear Time Jonathan Kelner, Jerry Li, Allen X. Liu, Aaron Sidford, Kevin Tian
NeurIPS 2023 Structured Semidefinite Programming for Recovering Structured Preconditioners Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
NeurIPSW 2022 Semi-Random Sparse Recovery in Nearly-Linear Time Jonathan Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
COLT 2022 Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods Yujia Jin, Aaron Sidford, Kevin Tian
NeurIPS 2021 List-Decodable Mean Estimation in Nearly-PCA Time Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
NeurIPS 2021 Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions Yin Tat Lee, Ruoqi Shen, Kevin Tian
NeurIPS 2021 Robust Regression Revisited: Acceleration and Improved Estimation Rates Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
COLT 2021 Structured Logconcave Sampling with a Restricted Gaussian Oracle Yin Tat Lee, Ruoqi Shen, Kevin Tian
NeurIPS 2020 Acceleration with a Ball Optimization Oracle Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
COLT 2020 Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Yin Tat Lee, Ruoqi Shen, Kevin Tian
NeurIPS 2020 Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing Arun Jambulapati, Jerry Li, Kevin Tian
NeurIPS 2019 A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport Arun Jambulapati, Aaron Sidford, Kevin Tian
NeurIPS 2019 Variance Reduction for Matrix Games Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
ICML 2018 CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions Kevin Tian, Teng Zhang, James Zou
NeurIPS 2017 Learning Populations of Parameters Kevin Tian, Weihao Kong, Gregory Valiant