Yu Cheng

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 50

Top Topics

Teaching Dimension

Low Rank Matrix

Gaussian Graphical Models

Nash Equilibria

Top Venues

Publications

Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. CoRR (2024)
Yu Cheng, Max Li, Honghao Lin, Zi-Yi Tai, David P. Woodruff, Jason Zhang
Tight Lower Bounds for Directed Cut Sparsification and Distributed Min-Cut. CoRR (2024)
Yu Cheng, Max Li, Honghao Lin, Zi-Yi Tai, David P. Woodruff, Jason Zhang
Tight Lower Bounds for Directed Cut Sparsification and Distributed Min-Cut. Proc. ACM Manag. Data 2 (2) (2024)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Efficiently Solving Turn-Taking Stochastic Games with Extensive-Form Correlation. EC (2023)
Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. NeurIPS (2023)
Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi
Outlier-Robust Sparse Estimation via Non-Convex Optimization. NeurIPS (2022)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Planning with Participation Constraints. AAAI (2022)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Efficient Algorithms for Planning with Participation Constraints. EC (2022)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Efficient Algorithms for Planning with Participation Constraints. CoRR (2022)
Yu Cheng, Honghao Lin
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time. ICLR (2021)
Ruoxu Cen, Yu Cheng, Debmalya Panigrahi, Kevin Sun
Sparsification of Directed Graphs via Cut Balance. ICALP (2021)
Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi
Outlier-Robust Sparse Estimation via Non-Convex Optimization. CoRR (2021)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Classification with Few Tests through Self-Selection. AAAI (2021)
Yu Cheng, Nick Gravin, Kamesh Munagala, Kangning Wang
A Simple Mechanism for a Budget-Constrained Buyer. ACM Trans. Economics and Comput. 9 (2) (2021)
Yu Cheng, Honghao Lin
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time. CoRR (2021)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Automated Mechanism Design for Classification with Partial Verification. AAAI (2021)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Automated Mechanism Design for Classification with Partial Verification. CoRR (2021)
Anilesh Kollagunta Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng, Kamesh Munagala
Fair for All: Best-effort Fairness Guarantees for Classification. AISTATS (2021)
Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
High-Dimensional Robust Mean Estimation via Gradient Descent. CoRR (2020)
Yu Cheng, Zhihao Jiang, Kamesh Munagala, Kangning Wang
Group Fairness in Committee Selection. ACM Trans. Economics and Comput. 8 (4) (2020)
Anilesh K. Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng, Kamesh Munagala
Fair for All: Best-effort Fairness Guarantees for Classification. CoRR (2020)
Yu Cheng, Debmalya Panigrahi, Kevin Sun
Sparsification of Balanced Directed Graphs. CoRR (2020)
Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
High-dimensional Robust Mean Estimation via Gradient Descent. ICML (2020)
Yu Cheng, Ilias Diakonikolas, Rong Ge, David P. Woodruff
Faster Algorithms for High-Dimensional Robust Covariance Estimation. CoRR (2019)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
When Samples Are Strategically Selected. ICML (2019)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
A Better Algorithm for Societal Tradeoffs. AAAI (2019)
Yu Cheng, Zhihao Jiang, Kamesh Munagala, Kangning Wang
Group Fairness in Committee Selection. EC (2019)
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Distinguishing Distributions When Samples Are Strategically Transformed. NeurIPS (2019)
Yu Cheng, Ilias Diakonikolas, Rong Ge
High-Dimensional Robust Mean Estimation in Nearly-Linear Time. SODA (2019)
Yu Cheng, Ilias Diakonikolas, Rong Ge, David P. Woodruff
Faster Algorithms for High-Dimensional Robust Covariance Estimation. COLT (2019)
Yu Cheng, Zhihao Jiang, Kamesh Munagala, Kangning Wang
Group Fairness in Committee Selection. CoRR (2019)
Yu Cheng, Ilias Diakonikolas, Rong Ge
High-Dimensional Robust Mean Estimation in Nearly-Linear Time. CoRR (2018)
Yu Cheng, Ilias Diakonikolas, Daniel Kane, Alistair Stewart
Robust Learning of Fixed-Structure Bayesian Networks. NeurIPS (2018)
Yu Cheng, Wade Hann-Caruthers, Omer Tamuz
A Deterministic Protocol for Sequential Asymptotic Learning. CoRR (2018)
Yu Cheng, Rong Ge
Non-Convex Matrix Completion Against a Semi-Random Adversary. CoRR (2018)
Yu Cheng, Shaddin Dughmi, David Kempe
On the Distortion of Voting With Multiple Representative Candidates. AAAI (2018)
Yu Cheng, Nick Gravin, Kamesh Munagala, Kangning Wang
A Simple Mechanism for a Budget-Constrained Buyer. CoRR (2018)
Yu Cheng, Nick Gravin, Kamesh Munagala, Kangning Wang
A Simple Mechanism for a Budget-Constrained Buyer. WINE (2018)
Yu Cheng, Rong Ge
Non-Convex Matrix Completion Against a Semi-Random Adversary. COLT (2018)
Yu Cheng, Wade Hann-Caruthers, Omer Tamuz
A Deterministic Protocol for Sequential Asymptotic Learning. ISIT (2018)
Yu Cheng, Shaddin Dughmi, David Kempe
Of the People: Voting Is More Effective with Representative Candidates. CoRR (2017)
Yu Cheng, Shaddin Dughmi, David Kempe
On the Distortion of Voting with Multiple Representative Candidates. CoRR (2017)
Yu Cheng, Ilias Diakonikolas, Alistair Stewart
Playing Anonymous Games using Simple Strategies. SODA (2017)
Xi Chen, Yu Cheng, Bo Tang
Well-Supported vs. Approximate Nash Equilibria: Query Complexity of Large Games. ITCS (2017)
Yu Cheng, Shaddin Dughmi, David Kempe
Of the People: Voting Is More Effective with Representative Candidates. EC (2017)
Xi Chen, Yu Cheng, Bo Tang
On the Recursive Teaching Dimension of VC Classes. NIPS (2016)
Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
Robust Learning of Fixed-Structure Bayesian Networks. CoRR (2016)
Yu Cheng, Ilias Diakonikolas, Alistair Stewart
Playing Anonymous Games using Simple Strategies. CoRR (2016)
Umang Bhaskar, Yu Cheng, Young Kun Ko, Chaitanya Swamy
Hardness Results for Signaling in Bayesian Zero-Sum and Network Routing Games. EC (2016)
Xi Chen, Yu Cheng, Bo Tang
A Note on Teaching for VC Classes. Electron. Colloquium Comput. Complex. 23 (2016)
Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng
Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification. COLT (2015)
Umang Bhaskar, Yu Cheng, Young Kun Ko, Chaitanya Swamy
Near-Optimal Hardness Results for Signaling in Bayesian Games. CoRR (2015)
Xi Chen, Yu Cheng, Bo Tang
Well-Supported versus Approximate Nash Equilibria: Query Complexity of Large Games. CoRR (2015)
Yu Cheng, Ho Yee Cheung, Shaddin Dughmi, Ehsan Emamjomeh-Zadeh, Li Han, Shang-Hua Teng
Mixture Selection, Mechanism Design, and Signaling. FOCS (2015)
Yu Cheng, Ho Yee Cheung, Shaddin Dughmi, Ehsan Emamjomeh-Zadeh, Li Han, Shang-Hua Teng
Mixture Selection, Mechanism Design, and Signaling. CoRR (2015)
Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng
Spectral Sparsification of Random-Walk Matrix Polynomials. CoRR (2015)
Yu Cheng, Ho Yee Cheung, Shaddin Dughmi, Shang-Hua Teng
Signaling in Quasipolynomial time. CoRR (2014)
Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng
Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models. CoRR (2014)