Yi Li

Orcid: 0000-0002-6420-653X

Affiliations:
  • Nanyang Technological University, Singapore
  • Facebook
  • Max Planck Institute for Informatics, Saarbrücken, Germany


According to our database1, Yi Li authored at least 43 papers between 2012 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
The ℓ<sub><i>p</i></sub>-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines.
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Learning the Positions in CountSketch.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Higher Lower Bounds for Sparse Oblivious Subspace Embeddings.
CoRR, 2022

The 𝓁<sub>p</sub>-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines.
CoRR, 2022

Expected size of random Tukey layers and convex layers.
Comput. Geom., 2022

Lower Bounds for Sparse Oblivious Subspace Embeddings.
Proceedings of the PODS '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Online Active Regression.
Proceedings of the International Conference on Machine Learning, 2022

Streaming Algorithms with Large Approximation Factors.
Proceedings of the Approximation, 2022

2021
Tight Bounds for the Subspace Sketch Problem with Applications.
SIAM J. Comput., 2021

Exponentially Improved Dimensionality Reduction for 𝓁<sub>1</sub>: Subspace Embeddings and Independence Testing.
CoRR, 2021

Learning-Augmented Sketches for Hessians.
CoRR, 2021

Geometric Cover with Outliers Removal.
Proceedings of the 38th International Symposium on Theoretical Aspects of Computer Science, 2021

Single Pass Entrywise-Transformed Low Rank Approximation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Exponentially Improved Dimensionality Reduction for l1: Subspace Embeddings and Independence Testing.
Proceedings of the Conference on Learning Theory, 2021

Learning to Cluster via Same-Cluster Queries.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

The Product of Gaussian Matrices Is Close to Gaussian.
Proceedings of the Approximation, 2021

2020
Sublinear-Time Algorithms for Compressive Phase Retrieval.
IEEE Trans. Inf. Theory, 2020

The Expected Size of Random Convex Layers and Convex Shells.
CoRR, 2020

Minimum Enclosing Parallelogram with Outliers.
CoRR, 2020

Input-Sparsity Low Rank Approximation in Schatten Norm.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning-Augmented Data Stream Algorithms.
Proceedings of the 8th International Conference on Learning Representations, 2020

Deterministic Sparse Fourier Transform with an ℓ<sub>∞</sub> Guarantee.
Proceedings of the 47th International Colloquium on Automata, Languages, and Programming, 2020

Streaming Complexity of SVMs.
Proceedings of the Approximation, 2020

2019
Distributed Partial Clustering.
ACM Trans. Parallel Comput., 2019

On Approximating Matrix Norms in Data Streams.
SIAM J. Comput., 2019

Deterministic Sparse Fourier Transform with an ell_infty Guarantee.
CoRR, 2019

Testing Matrix Rank, Optimally.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

2018
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order.
Proceedings of the 35th International Conference on Machine Learning, 2018

On Low-Risk Heavy Hitters and Sparse Recovery Schemes.
Proceedings of the Approximation, 2018

Deterministic Heavy Hitters with Sublinear Query Time.
Proceedings of the Approximation, 2018

2017
For-All Sparse Recovery in Near-Optimal Time.
ACM Trans. Algorithms, 2017

Embeddings of Schatten Norms with Applications to Data Streams.
Proceedings of the 44th International Colloquium on Automata, Languages, and Programming, 2017

2016
On approximating functions of the singular values in a stream.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

New Characterizations in Turnstile Streams with Applications.
Proceedings of the 31st Conference on Computational Complexity, 2016

Tight Bounds for Sketching the Operator Norm, Schatten Norms, and Subspace Embeddings.
Proceedings of the Approximation, 2016

2015
What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid.
Algorithmica, 2015

2014
On the Communication Complexity of Linear Algebraic Problems in the Message Passing Model.
Proceedings of the Distributed Computing - 28th International Symposium, 2014

Turnstile streaming algorithms might as well be linear sketches.
Proceedings of the Symposium on Theory of Computing, 2014

On Sketching Matrix Norms and the Top Singular Vector.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Improved testing of low rank matrices.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013
Sublinear Time Algorithms for the Sparse Recovery Problem.
PhD thesis, 2013

A Tight Lower Bound for High Frequency Moment Estimation with Small Error.
Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2013

2012
Approximate Sparse Recovery: Optimizing Time and Measurements.
SIAM J. Comput., 2012


  Loading...