Kevin Tian

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 73

Top Topics

Semidefinite Program

Algorithmic Aspects

Top Venues

Publications

Lunjia Hu, Kevin Tian, Chutong Yang
Testing Calibration in Subquadratic Time. CoRR (2024)
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
Black-Box k-to-1-PCA Reductions: Theory and Applications. COLT (2024)
Arun Jambulapati, Aaron Sidford, Kevin Tian
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. COLT (2024)
Arun Jambulapati, Aaron Sidford, Kevin Tian
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. CoRR (2024)
Ewin Tang, Kevin Tian
A CS guide to the quantum singular value transformation. SOSA (2024)
Hilal Asi, Daogao Liu, Kevin Tian
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions. CoRR (2024)
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
Black-Box k-to-1-PCA Reductions: Theory and Applications. CoRR (2024)
Arun Jambulapati, Victor Reis, Kevin Tian
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. SODA (2024)
Ewin Tang, Kevin Tian
A CS guide to the quantum singular value transformation. CoRR (2023)
Adam Bouland, Yosheb Getachew, Yujia Jin, Aaron Sidford, Kevin Tian
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling. CoRR (2023)
Arun Jambulapati, Kevin Tian
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations. NeurIPS (2023)
Jonathan A. Kelner, Jerry Li, Allen X. Liu, Aaron Sidford, Kevin Tian
Semi-Random Sparse Recovery in Nearly-Linear Time. COLT (2023)
Nima Anari, Callum Burgess, Kevin Tian, Thuy-Duong Vuong
Quadratic Speedups in Parallel Sampling from Determinantal Distributions. SPAA (2023)
Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
ReSQueing Parallel and Private Stochastic Convex Optimization. CoRR (2023)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Matrix Completion in Almost-Verification Time. CoRR (2023)
Arun Jambulapati, Victor Reis, Kevin Tian
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS (2023)
Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
ReSQueing Parallel and Private Stochastic Convex Optimization. FOCS (2023)
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. CoRR (2023)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Matrix Completion in Almost-Verification Time. FOCS (2023)
Adam Bouland, Yosheb M. Getachew, Yujia Jin, Aaron Sidford, Kevin Tian
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling. ICML (2023)
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. COLT (2023)
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
Private Convex Optimization in General Norms. SODA (2023)
Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space. SODA (2022)
Yujia Jin, Aaron Sidford, Kevin Tian
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods. CoRR (2022)
Nima Anari, Callum Burgess, Kevin Tian, Thuy-Duong Vuong
Improved Sampling-to-Counting Reductions in High-Dimensional Expanders and Faster Parallel Determinantal Sampling. CoRR (2022)
Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. ICALP (2022)
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
Private Convex Optimization in General Norms. CoRR (2022)
Yujia Jin, Aaron Sidford, Kevin Tian
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods. COLT (2022)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR (2022)
Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
Clustering mixture models in almost-linear time via list-decodable mean estimation. STOC (2022)
Yin Tat Lee, Ruoqi Shen, Kevin Tian
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. NeurIPS (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS (2021)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. CoRR (2021)
Yin Tat Lee, Ruoqi Shen, Kevin Tian
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. CoRR (2021)
Yin Tat Lee, Ruoqi Shen, Kevin Tian
Structured Logconcave Sampling with a Restricted Gaussian Oracle. COLT (2021)
Michael B. Cohen, Aaron Sidford, Kevin Tian
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration. ITCS (2021)
Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
List-Decodable Mean Estimation in Nearly-PCA Time. NeurIPS (2021)
Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
Acceleration with a Ball Optimization Oracle. NeurIPS (2020)
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
Coordinate Methods for Matrix Games. FOCS (2020)
Yin Tat Lee, Ruoqi Shen, Kevin Tian
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. CoRR (2020)
Yin Tat Lee, Ruoqi Shen, Kevin Tian
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. COLT (2020)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
List-Decodable Mean Estimation in Nearly-PCA Time. CoRR (2020)
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
Coordinate Methods for Matrix Games. CoRR (2020)
Arun Jambulapati, Jerry Li, Kevin Tian
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. CoRR (2020)
Arun Jambulapati, Jerry Li, Kevin Tian
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. NeurIPS (2020)
Shuo Liu, Lisa Singh, Kevin Tian
Information Exposure From Relational Background Knowledge on Social Media. DSAA (2020)
Ruoqi Shen, Kevin Tian, Yin Tat Lee
Composite Logconcave Sampling with a Restricted Gaussian Oracle. CoRR (2020)
Michael B. Cohen, Aaron Sidford, Kevin Tian
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration. CoRR (2020)
Yin Tat Lee, Ruoqi Shen, Kevin Tian
Structured Logconcave Sampling with a Restricted Gaussian Oracle. CoRR (2020)
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent. CoRR (2020)
Yujia Jin, Aaron Sidford, Kevin Tian
Semi-Streaming Bipartite Matching in Fewer Passes and Less Space. CoRR (2020)
Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang
Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise. CoRR (2020)
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
Positive semidefinite programming: mixed, parallel, and width-independent. STOC (2020)
Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
Acceleration with a Ball Optimization Oracle. CoRR (2020)
Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian
A Rank-1 Sketch for Matrix Multiplicative Weights. COLT (2019)
Arun Jambulapati, Aaron Sidford, Kevin Tian
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport. NeurIPS (2019)
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
Variance Reduction for Matrix Games. NeurIPS (2019)
Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian
A Rank-1 Sketch for Matrix Multiplicative Weights. CoRR (2019)
Arun Jambulapati, Aaron Sidford, Kevin Tian
A Direct Õ(1/ε) Iteration Parallel Algorithm for Optimal Transport. CoRR (2019)
Sampath Kannan, Kevin Tian
Locating Errors in Faulty Formulas. ACM Trans. Algorithms 15 (3) (2019)
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
Variance Reduction for Matrix Games. CoRR (2019)
Kevin Tian, Teng Zhang, James Zou
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. CoRR (2018)
Aaron Sidford, Kevin Tian
Regression and Faster Approximate Maximum Flow. CoRR (2018)
Aaron Sidford, Kevin Tian
Coordinate Methods for Accelerating ℓ∞ Regression and Faster Approximate Maximum Flow. FOCS (2018)
Kevin Tian, Teng Zhang, James Zou
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. ICML (2018)
Yuchun Guo, Kevin Tian, Haoyang Zeng, David K. Gifford
K-mer Set Memory (KSM) Motif Representation Enables Accurate Prediction of the Impact of Regulatory Variants. RECOMB (2017)
Kevin Tian, Weihao Kong, Gregory Valiant
Optimally Learning Populations of Parameters. CoRR (2017)
Kevin Tian, Weihao Kong, Gregory Valiant
Learning Populations of Parameters. NIPS (2017)
Deeparnab Chakrabarty, Sampath Kannan, Kevin Tian
Detecting Character Dependencies in Stochastic Models of Evolution. J. Comput. Biol. 23 (3) (2016)
Lisa Singh, Grace Hui Yang, Micah Sherr, Andrew Hian-Cheong, Kevin Tian, Janet Zhu, Sicong Zhang
Public Information Exposure Detection: Helping Users Understand Their Web Footprints. ASONAM (2015)
Lisa Singh, Grace Hui Yang, Micah Sherr, Yifang Wei, Andrew Hian-Cheong, Kevin Tian, Janet Zhu, Sicong Zhang, Tavish Vaidya, Elchin Asgarli
Helping Users Understand Their Web Footprints. WWW (Companion Volume) (2015)
Rajeev Alur, Sampath Kannan, Kevin Tian, Yifei Yuan
On the Complexity of Shortest Path Problems on Discounted Cost Graphs. LATA (2013)
Hui Lv, Yaozu Dong, Jiangang Duan, Kevin Tian
Virtualization challenges: a view from server consolidation perspective. VEE (2012)
Nathaniel Dean, Alexandra Ilic, Ignacio Ramírez, Jian Shen, Kevin Tian
On the Power Dominating Sets of Hypercubes. CSE (2011)
Yaozu Dong, Jinquan Dai, Zhiteng Huang, Haibing Guan, Kevin Tian, Yunhong Jiang
Towards high-quality I/O virtualization. SYSTOR (2009)