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2020 – today
- 2024
[c41]Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian:
Black-Box k-to-1-PCA Reductions: Theory and Applications. COLT 2024: 2564-2607- [c40]Arun Jambulapati, Aaron Sidford, Kevin Tian:
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. COLT 2024: 2608-2643 - [c39]Arun Jambulapati, Victor Reis, Kevin Tian:
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. SODA 2024: 5169-5208 - [c38]Ewin Tang, Kevin Tian:
A CS guide to the quantum singular value transformation. SOSA 2024: 121-143 - [i36]Lunjia Hu, Kevin Tian, Chutong Yang:
Testing Calibration in Subquadratic Time. CoRR abs/2402.13187 (2024) - [i35]Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian:
Black-Box k-to-1-PCA Reductions: Theory and Applications. CoRR abs/2403.03905 (2024) - [i34]Hilal Asi, Daogao Liu, Kevin Tian:
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions. CoRR abs/2406.02789 (2024) - [i33]Arun Jambulapati, Aaron Sidford, Kevin Tian:
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. CoRR abs/2406.07373 (2024) - 2023
- [c37]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. COLT 2023: 2352-2398 - [c36]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: 2399-2439 - [c35]Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian:
ReSQueing Parallel and Private Stochastic Convex Optimization. FOCS 2023: 2031-2058 - [c34]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. FOCS 2023: 2102-2128 - [c33]Adam Bouland, Yosheb M. Getachew, Yujia Jin, Aaron Sidford, Kevin Tian:
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling. ICML 2023: 2932-2952 - [c32]Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS 2023 - [c31]Arun Jambulapati, Kevin Tian:
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations. NeurIPS 2023 - [c30]Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian:
Private Convex Optimization in General Norms. SODA 2023: 5068-5089 - [c29]Nima Anari
, Callum Burgess, Kevin Tian, Thuy-Duong Vuong:
Quadratic Speedups in Parallel Sampling from Determinantal Distributions. SPAA 2023: 367-377 - [i32]Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian:
ReSQueing Parallel and Private Stochastic Convex Optimization. CoRR abs/2301.00457 (2023) - [i31]Adam Bouland, Yosheb Getachew, Yujia Jin, Aaron Sidford, Kevin Tian:
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling. CoRR abs/2301.03763 (2023) - [i30]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 abs/2302.06085 (2023) - [i29]Ewin Tang, Kevin Tian:
A CS guide to the quantum singular value transformation. CoRR abs/2302.14324 (2023) - [i28]Arun Jambulapati, Victor Reis, Kevin Tian:
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. CoRR abs/2305.08434 (2023) - [i27]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. CoRR abs/2308.03661 (2023) - [i26]Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR abs/2310.18265 (2023) - 2022
- [b1]Kevin Tian:
Iterative methods for structured algorithmic data science. Stanford University, USA, 2022 - [c28]Yujia Jin, Aaron Sidford, Kevin Tian:
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods. COLT 2022: 4362-4415 - [c27]Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian:
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. ICALP 2022: 77:1-77:20 - [c26]Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian:
Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space. SODA 2022: 627-669 - [c25]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: 1262-1275 - [i25]Yujia Jin, Aaron Sidford, Kevin Tian:
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods. CoRR abs/2202.04640 (2022) - [i24]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR abs/2203.04002 (2022) - [i23]Nima Anari, Callum Burgess, Kevin Tian, Thuy-Duong Vuong:
Improved Sampling-to-Counting Reductions in High-Dimensional Expanders and Faster Parallel Determinantal Sampling. CoRR abs/2203.11190 (2022) - [i22]Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian:
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. CoRR abs/2204.12721 (2022) - [i21]Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian:
Private Convex Optimization in General Norms. CoRR abs/2207.08347 (2022) - 2021
- [c24]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Structured Logconcave Sampling with a Restricted Gaussian Oracle. COLT 2021: 2993-3050 - [c23]Michael B. Cohen, Aaron Sidford, Kevin Tian:
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration. ITCS 2021: 62:1-62:18 - [c22]Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian:
Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS 2021: 4475-4488 - [c21]Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
List-Decodable Mean Estimation in Nearly-PCA Time. NeurIPS 2021: 10195-10208 - [c20]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. NeurIPS 2021: 18812-18824 - [i20]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. CoRR abs/2106.05480 (2021) - [i19]Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. CoRR abs/2106.08537 (2021) - [i18]Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian:
Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR abs/2106.11938 (2021) - 2020
- [c19]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. COLT 2020: 2565-2597 - [c18]Shuo Liu, Lisa Singh, Kevin Tian:
Information Exposure From Relational Background Knowledge on Social Media. DSAA 2020: 282-291 - [c17]Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian:
Coordinate Methods for Matrix Games. FOCS 2020: 283-293 - [c16]Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian:
Acceleration with a Ball Optimization Oracle. NeurIPS 2020 - [c15]Arun Jambulapati, Jerry Li, Kevin Tian:
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. NeurIPS 2020 - [c14]Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian:
Positive semidefinite programming: mixed, parallel, and width-independent. STOC 2020: 789-802 - [i17]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. CoRR abs/2002.04121 (2020) - [i16]Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian:
Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent. CoRR abs/2002.04830 (2020) - [i15]Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian:
Acceleration with a Ball Optimization Oracle. CoRR abs/2003.08078 (2020) - [i14]Ruoqi Shen, Kevin Tian, Yin Tat Lee:
Composite Logconcave Sampling with a Restricted Gaussian Oracle. CoRR abs/2006.05976 (2020) - [i13]Arun Jambulapati, Jerry Li, Kevin Tian:
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. CoRR abs/2006.06980 (2020) - [i12]Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang:
Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise. CoRR abs/2008.01722 (2020) - [i11]Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian:
Coordinate Methods for Matrix Games. CoRR abs/2009.08447 (2020) - [i10]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Structured Logconcave Sampling with a Restricted Gaussian Oracle. CoRR abs/2010.03106 (2020) - [i9]Yujia Jin, Aaron Sidford, Kevin Tian:
Semi-Streaming Bipartite Matching in Fewer Passes and Less Space. CoRR abs/2011.03495 (2020) - [i8]Michael B. Cohen, Aaron Sidford, Kevin Tian:
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration. CoRR abs/2011.06572 (2020) - [i7]Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
List-Decodable Mean Estimation in Nearly-PCA Time. CoRR abs/2011.09973 (2020)
2010 – 2019
- 2019
- [j2]Sampath Kannan, Kevin Tian:
Locating Errors in Faulty Formulas. ACM Trans. Algorithms 15(3): 34:1-34:13 (2019) - [c13]Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian:
A Rank-1 Sketch for Matrix Multiplicative Weights. COLT 2019: 589-623 - [c12]Arun Jambulapati, Aaron Sidford, Kevin Tian:
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport. NeurIPS 2019: 11355-11366 - [c11]Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian:
Variance Reduction for Matrix Games. NeurIPS 2019: 11377-11388 - [i6]Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian:
A Rank-1 Sketch for Matrix Multiplicative Weights. CoRR abs/1903.02675 (2019) - [i5]Arun Jambulapati, Aaron Sidford, Kevin Tian:
A Direct Õ(1/ε) Iteration Parallel Algorithm for Optimal Transport. CoRR abs/1906.00618 (2019) - [i4]Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian:
Variance Reduction for Matrix Games. CoRR abs/1907.02056 (2019) - 2018
- [c10]Aaron Sidford, Kevin Tian:
Coordinate Methods for Accelerating ℓ∞ Regression and Faster Approximate Maximum Flow. FOCS 2018: 922-933 - [c9]Kevin Tian, Teng Zhang, James Zou:
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. ICML 2018: 4933-4942 - [i3]Kevin Tian, Teng Zhang, James Zou:
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. CoRR abs/1802.07839 (2018) - [i2]Aaron Sidford, Kevin Tian:
Coordinate Methods for Accelerating 𝓁∞ Regression and Faster Approximate Maximum Flow. CoRR abs/1808.01278 (2018) - 2017
- [c8]Kevin Tian, Weihao Kong, Gregory Valiant:
Learning Populations of Parameters. NIPS 2017: 5778-5787 - [c7]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: 372-374 - [i1]Kevin Tian, Weihao Kong, Gregory Valiant:
Optimally Learning Populations of Parameters. CoRR abs/1709.02707 (2017) - 2016
- [j1]Deeparnab Chakrabarty, Sampath Kannan, Kevin Tian:
Detecting Character Dependencies in Stochastic Models of Evolution. J. Comput. Biol. 23(3): 180-191 (2016) - 2015
- [c6]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: 153-161 - [c5]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: 117-118 - 2013
- [c4]Rajeev Alur, Sampath Kannan, Kevin Tian, Yifei Yuan:
On the Complexity of Shortest Path Problems on Discounted Cost Graphs. LATA 2013: 44-55 - 2012
- [c3]Hui Lv, Yaozu Dong, Jiangang Duan, Kevin Tian:
Virtualization challenges: a view from server consolidation perspective. VEE 2012: 15-26 - 2011
- [c2]Nathaniel Dean, Alexandra Ilic, Ignacio Ramírez, Jian Shen, Kevin Tian:
On the Power Dominating Sets of Hypercubes. CSE 2011: 488-491
2000 – 2009
- 2009
- [c1]Yaozu Dong, Jinquan Dai, Zhiteng Huang, Haibing Guan, Kevin Tian, Yunhong Jiang:
Towards high-quality I/O virtualization. SYSTOR 2009: 12
Coauthor Index
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last updated on 2024-08-05 20:23 CEST by the dblp team
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