Kevin Tian

101 papers A* 37A 1B 5C 1Misc 1Journal 51Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Combinatorial Sparse PCA Beyond the Spiked Identity Model.
CoRR
Syamantak Kumar, Purnamrita Sarkar, Kevin Tian, Peiyuan Zhang
2026 J jnl
Functional Stochastic Localization.
CoRR
Anming Gu, Bobby Shi, Kevin Tian
2026 J jnl
Separating Oblivious and Adaptive Models of Variable Selection.
CoRR
Ziyun Chen, Jerry Li, Kevin Tian, Yusong Zhu
2026 J jnl
Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction.
CoRR
Lunjia Hu, Kevin Tian, Chutong Yang
2025 A* conf
Eulerian Graph Sparsification by Effective Resistance Decomposition.
SODA
Arun Jambulapati, Sushant Sachdeva, Aaron Sidford, Kevin Tian, Yibin Zhao
2025 J jnl
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random.
CoRR
Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian
2025 J jnl
More of the Same: Persistent Representational Harms Under Increased Representation.
CoRR
Jennifer Mickel, Maria De-Arteaga, Leqi Liu, Kevin Tian
2025 A* conf
Omnipredicting Single-Index Models with Multi-index Models.
STOC
Lunjia Hu, Kevin Tian, Chutong Yang
2025 J jnl
Perspectives on Stochastic Localization.
CoRR
Bobby Shi, Kevin Tian, Matthew S. Zhang
2025 J jnl
Private Geometric Median in Nearly-Linear Time.
CoRR
Syamantak Kumar, Daogao Liu, Kevin Tian, Chutong Yang
2025 A* conf
Radial Isotropic Position via an Implicit Newton's Method.
FOCS
Arun Jambulapati, Jonathan Li, Kevin Tian
2025 J jnl
Radial Isotropic Position via an Implicit Newton's Method.
CoRR
Arun Jambulapati, Jonathan Li, Kevin Tian
2025 A* conf
Spike-and-Slab Posterior Sampling in High Dimensions.
COLT
Symantak Kumar, Purnamrita Sarkar, Kevin Tian, Yusong Zhu
2025 J jnl
Spike-and-Slab Posterior Sampling in High Dimensions.
CoRR
Syamantak Kumar, Purnamrita Sarkar, Kevin Tian, Yusong Zhu
2025 J jnl
The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination.
CoRR
Adam R. Klivans, Konstantinos Stavropoulos, Kevin Tian, Arsen Vasilyan
2024 — conf
A CS guide to the quantum singular value transformation.
SOSA
Ewin Tang, Kevin Tian
2024 A* conf
Black-Box k-to-1-PCA Reductions: Theory and Applications.
COLT
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
2024 J jnl
Black-Box k-to-1-PCA Reductions: Theory and Applications.
CoRR
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
2024 A* conf
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization.
COLT
Arun Jambulapati, Aaron Sidford, Kevin Tian
2024 J jnl
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization.
CoRR
Arun Jambulapati, Aaron Sidford, Kevin Tian
2024 J jnl
Eulerian Graph Sparsification by Effective Resistance Decomposition.
CoRR
Arun Jambulapati, Sushant Sachdeva, Aaron Sidford, Kevin Tian, Yibin Zhao
2024 A* conf
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random.
NeurIPS
Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian
2024 A* conf
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory.
SODA
Arun Jambulapati, Victor Reis, Kevin Tian
2024 J jnl
Omnipredicting Single-Index Models with Multi-Index Models.
CoRR
Lunjia Hu, Kevin Tian, Chutong Yang
2024 A* conf
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions.
NeurIPS
Hilal Asi, Daogao Liu, Kevin Tian
2024 J jnl
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions.
CoRR
Hilal Asi, Daogao Liu, Kevin Tian
2024 A* conf
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting.
NeurIPS
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
2024 A* conf
Testing Calibration in Nearly-Linear Time.
NeurIPS
Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang
2024 J jnl
Testing Calibration in Subquadratic Time.
CoRR
Lunjia Hu, Kevin Tian, Chutong Yang
2023 J jnl
A CS guide to the quantum singular value transformation.
CoRR
Ewin Tang, Kevin Tian
2023 A* conf
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler.
COLT
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
2023 J jnl
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler.
CoRR
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
2023 J jnl
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory.
CoRR
Arun Jambulapati, Victor Reis, Kevin Tian
2023 A* conf
Matrix Completion in Almost-Verification Time.
FOCS
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
2023 J jnl
Matrix Completion in Almost-Verification Time.
CoRR
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
2023 A* conf
Private Convex Optimization in General Norms.
SODA
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
2023 B conf
Quadratic Speedups in Parallel Sampling from Determinantal Distributions.
SPAA
Nima Anari, Callum Burgess, Kevin Tian, Thuy-Duong Vuong
2023 A* conf
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling.
ICML
Adam Bouland, Yosheb M. Getachew, Yujia Jin, Aaron Sidford, Kevin Tian
2023 J jnl
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling.
CoRR
Adam Bouland, Yosheb Getachew, Yujia Jin, Aaron Sidford, Kevin Tian
2023 A* conf
ReSQueing Parallel and Private Stochastic Convex Optimization.
FOCS
Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
2023 J jnl
ReSQueing Parallel and Private Stochastic Convex Optimization.
CoRR
Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
2023 A* conf
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations.
NeurIPS
Arun Jambulapati, Kevin Tian
2023 A* conf
Semi-Random Sparse Recovery in Nearly-Linear Time.
COLT
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
2023 A* conf
Structured Semidefinite Programming for Recovering Structured Preconditioners.
NeurIPS
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023 J jnl
Structured Semidefinite Programming for Recovering Structured Preconditioners.
CoRR
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2022 A* conf
Clustering mixture models in almost-linear time via list-decodable mean estimation.
STOC
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2022 J jnl
Improved Sampling-to-Counting Reductions in High-Dimensional Expanders and Faster Parallel Determinantal Sampling.
CoRR
Nima Anari, Callum Burgess, Kevin Tian, Thuy-Duong Vuong
2022 — —
Iterative methods for structured algorithmic data science.
Kevin Tian
2022 J jnl
Private Convex Optimization in General Norms.
CoRR
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian
2022 A* conf
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching.
ICALP
Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
2022 J jnl
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching.
CoRR
Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
2022 J jnl
Semi-Random Sparse Recovery in Nearly-Linear Time.
CoRR
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
2022 A* conf
Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space.
SODA
Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
2022 A* conf
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods.
COLT
Yujia Jin, Aaron Sidford, Kevin Tian
2022 J jnl
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods.
CoRR
Yujia Jin, Aaron Sidford, Kevin Tian
2021 J jnl
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation.
CoRR
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2021 A* conf
List-Decodable Mean Estimation in Nearly-PCA Time.
NeurIPS
Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2021 A* conf
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions.
NeurIPS
Yin Tat Lee, Ruoqi Shen, Kevin Tian
2021 J jnl
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions.
CoRR
Yin Tat Lee, Ruoqi Shen, Kevin Tian
2021 A conf
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration.
ITCS
Michael B. Cohen, Aaron Sidford, Kevin Tian
2021 A* conf
Robust Regression Revisited: Acceleration and Improved Estimation Rates.
NeurIPS
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
2021 J jnl
Robust Regression Revisited: Acceleration and Improved Estimation Rates.
CoRR
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
2021 A* conf
Structured Logconcave Sampling with a Restricted Gaussian Oracle.
COLT
Yin Tat Lee, Ruoqi Shen, Kevin Tian
2020 A* conf
Acceleration with a Ball Optimization Oracle.
NeurIPS
Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
2020 J jnl
Acceleration with a Ball Optimization Oracle.
CoRR
Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
2020 J jnl
Composite Logconcave Sampling with a Restricted Gaussian Oracle.
CoRR
Ruoqi Shen, Kevin Tian, Yin Tat Lee
2020 A* conf
Coordinate Methods for Matrix Games.
FOCS
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
2020 J jnl
Coordinate Methods for Matrix Games.
CoRR
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
2020 B conf
Information Exposure From Relational Background Knowledge on Social Media.
DSAA
Shuo Liu, Lisa Singh, Kevin Tian
2020 J jnl
List-Decodable Mean Estimation in Nearly-PCA Time.
CoRR
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2020 A* conf
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo.
COLT
Yin Tat Lee, Ruoqi Shen, Kevin Tian
2020 J jnl
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo.
CoRR
Yin Tat Lee, Ruoqi Shen, Kevin Tian
2020 J jnl
Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent.
CoRR
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
2020 A* conf
Positive semidefinite programming: mixed, parallel, and width-independent.
STOC
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
2020 J jnl
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration.
CoRR
Michael B. Cohen, Aaron Sidford, Kevin Tian
2020 A* conf
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing.
NeurIPS
Arun Jambulapati, Jerry Li, Kevin Tian
2020 J jnl
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing.
CoRR
Arun Jambulapati, Jerry Li, Kevin Tian
2020 J jnl
Semi-Streaming Bipartite Matching in Fewer Passes and Less Space.
CoRR
Yujia Jin, Aaron Sidford, Kevin Tian
2020 J jnl
Structured Logconcave Sampling with a Restricted Gaussian Oracle.
CoRR
Yin Tat Lee, Ruoqi Shen, Kevin Tian
2020 J jnl
Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise.
CoRR
Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang
2019 J jnl
A Direct Õ(1/ε) Iteration Parallel Algorithm for Optimal Transport.
CoRR
Arun Jambulapati, Aaron Sidford, Kevin Tian
2019 A* conf
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport.
NeurIPS
Arun Jambulapati, Aaron Sidford, Kevin Tian
2019 A* conf
A Rank-1 Sketch for Matrix Multiplicative Weights.
COLT
Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian
2019 J jnl
A Rank-1 Sketch for Matrix Multiplicative Weights.
CoRR
Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian
2019 J jnl
Locating Errors in Faulty Formulas.
ACM Trans. Algorithms
Sampath Kannan, Kevin Tian
2019 A* conf
Variance Reduction for Matrix Games.
NeurIPS
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
2019 J jnl
Variance Reduction for Matrix Games.
CoRR
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian
2018 A* conf
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions.
ICML
Kevin Tian, Teng Zhang, James Zou
2018 J jnl
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions.
CoRR
Kevin Tian, Teng Zhang, James Zou
2018 A* conf
Coordinate Methods for Accelerating ℓ∞ Regression and Faster Approximate Maximum Flow.
FOCS
Aaron Sidford, Kevin Tian
2018 J jnl
Coordinate Methods for Accelerating 𝓁
CoRR
Aaron Sidford, Kevin Tian
2017 B conf
K-mer Set Memory (KSM) Motif Representation Enables Accurate Prediction of the Impact of Regulatory Variants.
RECOMB
Yuchun Guo, Kevin Tian, Haoyang Zeng, David K. Gifford
2017 — conf
Learning Populations of Parameters.
NIPS
Kevin Tian, Weihao Kong, Gregory Valiant
2017 J jnl
Optimally Learning Populations of Parameters.
CoRR
Kevin Tian, Weihao Kong, Gregory Valiant
2016 J jnl
Detecting Character Dependencies in Stochastic Models of Evolution.
J. Comput. Biol.
Deeparnab Chakrabarty, Sampath Kannan, Kevin Tian
2015 — conf
Helping Users Understand Their Web Footprints.
WWW (Companion Volume)
Lisa Singh, Grace Hui Yang, Micah Sherr, Yifang Wei, Andrew Hian-Cheong, Kevin Tian, Janet Zhu, Sicong Zhang, Tavish Vaidya, Elchin Asgarli
2015 B conf
Public Information Exposure Detection: Helping Users Understand Their Web Footprints.
ASONAM
Lisa Singh, Grace Hui Yang, Micah Sherr, Andrew Hian-Cheong, Kevin Tian, Janet Zhu, Sicong Zhang
2013 C conf
On the Complexity of Shortest Path Problems on Discounted Cost Graphs.
LATA
Rajeev Alur, Sampath Kannan, Kevin Tian, Yifei Yuan
2012 B conf
Virtualization challenges: a view from server consolidation perspective.
VEE
Hui Lv, Yaozu Dong, Jiangang Duan, Kevin Tian
2011 — conf
On the Power Dominating Sets of Hypercubes.
CSE
Nathaniel Dean, Alexandra Ilic, Ignacio Ramírez, Jian Shen, Kevin Tian
2009 Misc conf
Towards high-quality I/O virtualization.
SYSTOR
Yaozu Dong, Jinquan Dai, Zhiteng Huang, Haibing Guan, Kevin Tian, Yunhong Jiang