| 2026 | COLT | Separating Oblivious and Adaptive Models of Variable Selection (Extended Abstract). | Ziyun Chen, Jerry Li, Kevin Tian, Yusong Zhu |
| 2026 | COLT | Functional Stochastic Localization. | Anming Gu, Bobby Shi, Kevin Tian |
| 2026 | COLT | Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction. | Lunjia Hu, Kevin Tian, Chutong Yang |
| 2026 | COLT | On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA. | Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar, Kevin Tian |
| 2025 | COLT | Spike-and-Slab Posterior Sampling in High Dimensions. | Symantak Kumar, Purnamrita Sarkar, Kevin Tian, Yusong Zhu |
| 2025 | FOCS | Radial Isotropic Position via an Implicit Newton's Method. | Arun Jambulapati, Jonathan Li, Kevin Tian |
| 2025 | SODA | Eulerian Graph Sparsification by Effective Resistance Decomposition. | Arun Jambulapati, Sushant Sachdeva, Aaron Sidford, Kevin Tian, Yibin Zhao |
| 2025 | STOC | Omnipredicting Single-Index Models with Multi-index Models. | Lunjia Hu, Kevin Tian, Chutong Yang |
| 2024 | COLT | Black-Box k-to-1-PCA Reductions: Theory and Applications. | Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian |
| 2024 | COLT | Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. | Arun Jambulapati, Aaron Sidford, Kevin Tian |
| 2024 | SODA | Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. | Arun Jambulapati, Victor Reis, Kevin Tian |
| 2023 | COLT | Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. | Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian |
| 2023 | COLT | Semi-Random Sparse Recovery in Nearly-Linear Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | FOCS | ReSQueing Parallel and Private Stochastic Convex Optimization. | Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian |
| 2023 | FOCS | Matrix Completion in Almost-Verification Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | ICML | Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling. | Adam Bouland, Yosheb M. Getachew, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2023 | SODA | Private Convex Optimization in General Norms. | Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian |
| 2023 | SPAA | Quadratic Speedups in Parallel Sampling from Determinantal Distributions. | Nima Anari, Callum Burgess, Kevin Tian, Thuy-Duong Vuong |
| 2022 | COLT | Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods. | Yujia Jin, Aaron Sidford, Kevin Tian |
| 2022 | ICALP | Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. | Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2022 | SODA | Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space. | Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2022 | STOC | Clustering mixture models in almost-linear time via list-decodable mean estimation. | Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian |
| 2021 | COLT | Structured Logconcave Sampling with a Restricted Gaussian Oracle. | Yin Tat Lee, Ruoqi Shen, Kevin Tian |
| 2020 | COLT | Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. | Yin Tat Lee, Ruoqi Shen, Kevin Tian |
| 2020 | DSAA | Information Exposure From Relational Background Knowledge on Social Media. | Shuo Liu, Lisa Singh, Kevin Tian |
| 2020 | FOCS | Coordinate Methods for Matrix Games. | Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2020 | STOC | Positive semidefinite programming: mixed, parallel, and width-independent. | Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian |
| 2019 | COLT | A Rank-1 Sketch for Matrix Multiplicative Weights. | Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian |
| 2018 | FOCS | Coordinate Methods for Accelerating ℓ∞ Regression and Faster Approximate Maximum Flow. | Aaron Sidford, Kevin Tian |
| 2018 | ICML | CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. | Kevin Tian, Teng Zhang, James Zou |
| 2017 | RECOMB | K-mer Set Memory (KSM) Motif Representation Enables Accurate Prediction of the Impact of Regulatory Variants. | Yuchun Guo, Kevin Tian, Haoyang Zeng, David K. Gifford |
| 2015 | WWW | Helping Users Understand Their Web Footprints. | Lisa Singh, Grace Hui Yang, Micah Sherr, Yifang Wei, Andrew Hian-Cheong, Kevin Tian, Janet Zhu, Sicong Zhang, Tavish Vaidya, Elchin Asgarli |
| 2013 | LATA | On the Complexity of Shortest Path Problems on Discounted Cost Graphs. | Rajeev Alur, Sampath Kannan, Kevin Tian, Yifei Yuan |
| 2012 | VEE | Virtualization challenges: a view from server consolidation perspective. | Hui Lv, Yaozu Dong, Jiangang Duan, Kevin Tian |
| 2009 | SYSTOR | Towards high-quality I/O virtualization. | Yaozu Dong, Jinquan Dai, Zhiteng Huang, Haibing Guan, Kevin Tian, Yunhong Jiang |