Approximate Sparse Recovery: Optimizing Time and Measurements. - Anna C. Gilbert; Yi Li 002; Ely Porat; Martin J. Strauss (SIAM J. Comput., 2012)

A Tight Lower Bound for High Frequency Moment Estimation with Small Error. - Yi Li 002; David P. Woodruff (APPROX-RANDOM, 2013)

Sublinear Time Algorithms for the Sparse Recovery Problem. - Yi Li 002 (2013)

Improved testing of low rank matrices. - Yi Li 002; Zhengyu Wang; David P. Woodruff (KDD, 2014)

On Sketching Matrix Norms and the Top Singular Vector. - Yi Li 002; Huy L. Nguyen; David P. Woodruff (SODA, 2014)

Turnstile streaming algorithms might as well be linear sketches. - Yi Li 002; Huy L. Nguyen; David P. Woodruff (STOC, 2014)

On the Communication Complexity of Linear Algebraic Problems in the Message Passing Model. - Yi Li 002; Xiaoming Sun 001; Chengu Wang; David P. Woodruff (DISC, 2014)

What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid. - Petros Boufounos; Volkan Cevher; Anna C. Gilbert; Yi Li 002; Martin J. Strauss (Algorithmica, 2015)

Tight Bounds for Sketching the Operator Norm, Schatten Norms, and Subspace Embeddings. - Yi Li 002; David P. Woodruff (APPROX-RANDOM, 2016)

New Characterizations in Turnstile Streams with Applications. - Yuqing Ai; Wei Hu; Yi Li 002; David P. Woodruff (CCC, 2016)

On approximating functions of the singular values in a stream. - Yi Li 002; David P. Woodruff (STOC, 2016)

Embeddings of Schatten Norms with Applications to Data Streams. - Yi Li 002; David P. Woodruff (ICALP, 2017)

For-All Sparse Recovery in Near-Optimal Time. - Anna C. Gilbert; Yi Li 002; Ely Porat; Martin J. Strauss (ACM Trans. Algorithms, 2017)

Deterministic Heavy Hitters with Sublinear Query Time. - Yi Li 002; Vasileios Nakos (APPROX-RANDOM, 2018)

On Low-Risk Heavy Hitters and Sparse Recovery Schemes. - Yi Li 002; Vasileios Nakos; David P. Woodruff (APPROX-RANDOM, 2018)

Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order. - Vladimir Braverman; Stephen R. Chestnut; Robert Krauthgamer; Yi Li 002; David P. Woodruff; Lin F. Yang (ICML, 2018)

Testing Matrix Rank, Optimally. - Maria-Florina Balcan; Yi Li 002; David P. Woodruff; Hongyang Zhang 001 (SODA, 2019)

Deterministic Sparse Fourier Transform with an ell_infty Guarantee. - Yi Li 002; Vasileios Nakos (CoRR, 2019)

On Approximating Matrix Norms in Data Streams. - Yi Li 002; Huy L. Nguyen; David P. Woodruff (SIAM J. Comput., 2019)

Distributed Partial Clustering. - Sudipto Guha; Yi Li 002; Qin Zhang 001 (ACM Trans. Parallel Comput., 2019)

Streaming Complexity of SVMs. - Alexandr Andoni; Collin Burns; Yi Li 002; Sepideh Mahabadi; David P. Woodruff (APPROX-RANDOM, 2020)

Deterministic Sparse Fourier Transform with an ℓ∞ Guarantee. - Yi Li 002; Vasileios Nakos (ICALP, 2020)

Learning-Augmented Data Stream Algorithms. - Tanqiu Jiang; Yi Li 002; Honghao Lin; Yisong Ruan; David P. Woodruff (ICLR, 2020)

Input-Sparsity Low Rank Approximation in Schatten Norm. - Yi Li 002; David P. Woodruff (ICML, 2020)

Nearly Linear Row Sampling Algorithm for Quantile Regression. - Yi Li 002; Ruosong Wang; Lin Yang 011; Hanrui Zhang 001 (ICML, 2020)

Minimum Enclosing Parallelogram with Outliers. - Zhengyang Guo; Yi Li 002 (CoRR, 2020)

The Expected Size of Random Convex Layers and Convex Shells. - Zhengyang Guo; Yi Li 002; Shaoyu Pei (CoRR, 2020)

Sublinear-Time Algorithms for Compressive Phase Retrieval. - Yi Li 002; Vasileios Nakos (IEEE Trans. Inf. Theory, 2020)

The Product of Gaussian Matrices Is Close to Gaussian. - Yi Li 002; David P. Woodruff (APPROX-RANDOM, 2021)

Learning to Cluster via Same-Cluster Queries. - Yi Li 002; Yan Song; Qin Zhang 001 (CIKM, 2021)

Exponentially Improved Dimensionality Reduction for l1: Subspace Embeddings and Independence Testing. - Yi Li 002; David P. Woodruff; Taisuke Yasuda 002 (COLT, 2021)

Single Pass Entrywise-Transformed Low Rank Approximation. - Yifei Jiang; Yi Li 002; Yiming Sun; Jiaxin Wang; David P. Woodruff (ICML, 2021)

Geometric Cover with Outliers Removal. - Zhengyang Guo; Yi Li 002 (STACS, 2021)

Learning-Augmented Sketches for Hessians. - Yi Li 002; Honghao Lin; David P. Woodruff (CoRR, 2021)

Exponentially Improved Dimensionality Reduction for 𝓁1: Subspace Embeddings and Independence Testing. - Yi Li 002; David P. Woodruff; Taisuke Yasuda 002 (CoRR, 2021)

Tight Bounds for the Subspace Sketch Problem with Applications. - Yi Li 002; Ruosong Wang; David P. Woodruff (SIAM J. Comput., 2021)

Streaming Algorithms with Large Approximation Factors. - Yi Li 002; Honghao Lin; David P. Woodruff; Yuheng Zhang (APPROX/RANDOM, 2022)

Online Active Regression. - Cheng Chen 015; Yi Li 002; Yiming Sun (ICML, 2022)

Lower Bounds for Sparse Oblivious Subspace Embeddings. - Yi Li 002; Mingmou Liu (PODS, 2022)

Expected size of random Tukey layers and convex layers. - Zhengyang Guo; Yi Li 002; Shaoyu Pei (Comput. Geom., 2022)

The 𝓁p-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines. - Yi Li 002; Honghao Lin; David P. Woodruff (CoRR, 2022)

Higher Lower Bounds for Sparse Oblivious Subspace Embeddings. - Yi Li 002; Mingmou Liu (CoRR, 2022)

ℓp-Regression in the Arbitrary Partition Model of Communication. - Yi Li 002; Honghao Lin; David P. Woodruff (COLT, 2023)

Learning the Positions in CountSketch. - Yi Li 002; Honghao Lin; Simin Liu; Ali Vakilian; David P. Woodruff (ICLR, 2023)

The ℓp-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines. - Yi Li 002; Honghao Lin; David P. Woodruff (SODA, 2023)

Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms. - Yi Li 002; Honghao Lin; David P. Woodruff (ICLR, 2024)

Faster Approximation Algorithms for k-Center via Data Reduction. - Arnold Filtser; Shaofeng H.-C. Jiang; Yi Li 002; Anurag Murty Naredla; Ioannis Psarros; Qiaoyuan Yang; Qin Zhang 001 (CoRR, 2025)