Justin Y. Chen

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 25

Top Topics

Worst Case Bounds

Differentially Private

Bipartite Matching

Top Venues

Publications

Justin Y. Chen, Piotr Indyk, David P. Woodruff
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. ITCS (2024)
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Constant Approximation for Individual Preference Stable Clustering. CoRR (2023)
Justin Y. Chen, Piotr Indyk, David P. Woodruff
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. CoRR (2023)
Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
Improved Frequency Estimation Algorithms with and without Predictions. CoRR (2023)
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. CoRR (2023)
Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal
Improved Space Bounds for Learning with Experts. CoRR (2023)
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
Data Structures for Density Estimation. CoRR (2023)
Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
Improved Frequency Estimation Algorithms with and without Predictions. NeurIPS (2023)
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. ACDA (2023)
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Constant Approximation for Individual Preference Stable Clustering. NeurIPS (2023)
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
Data Structures for Density Estimation. ICML (2023)
Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu
Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. SODA (2023)
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
Faster Fundamental Graph Algorithms via Learned Predictions. CoRR (2022)
Justin Y. Chen, Piotr Indyk, Tal Wagner
Streaming Algorithms for Support-Aware Histograms. ICML (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. CoRR (2022)
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
Triangle and Four Cycle Counting with Predictions in Graph Streams. CoRR (2022)
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR (2022)
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
Faster Fundamental Graph Algorithms via Learned Predictions. ICML (2022)
Justin Y. Chen, Shyam Narayanan, Yinzhan Xu
All-Pairs Shortest Path Distances with Differential Privacy: Improved Algorithms for Bounded and Unbounded Weights. CoRR (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk
(Optimal) Online Bipartite Matching with Degree Information. NeurIPS (2022)
Justin Y. Chen, Piotr Indyk, Tal Wagner
Streaming Algorithms for Support-Aware Histograms. CoRR (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. NeurIPS (2022)
Justin Y. Chen, Piotr Indyk
Online Bipartite Matching with Predicted Degrees. CoRR (2021)
Justin Y. Chen, Gregory Valiant, Paul Valiant
Worst-Case Analysis for Randomly Collected Data. NeurIPS (2020)
Justin Y. Chen, Gregory Valiant, Paul Valiant
How bad is worst-case data if you know where it comes from? CoRR (2019)