publications

As is the norm in theoretical computer science, authors are ordered alphabetically by last name for most papers. Exceptions use star(s) to indicate first author(s).

2025

  1. Scalable Private Partition Selection via Adaptive Weighting
    Preprint 2025
  2. Learning-Augmented Frequent Directions
    ICLR 2025 (Spotlight Award)

2024

  1. Differentially Private Gomory-Hu Trees
    Preprint 2024
  2. Evaluating the World Model Implicit in a Generative Model
    NeurIPS 2024 (Spotlight Award)
  3. Statistical-Computational Tradeoffs for Density Estimation
    NeurIPS 2024
  4. Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions
    Justin Y. ChenPiotr Indyk, and David P. Woodruff
    ITCS 2024

2023

  1. Improved Frequency Estimation Algorithms with and without Predictions
    NeurIPS 2023 (Spotlight Award)
  2. Constant Approximation for Individual Preference Stable Clustering
    NeurIPS 2023 (Spotlight Award)
  3. Data Structures for Density Estimation
    ICML 2023
  4. Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees
    ACDA 2023
  5. Improved Space Bounds for Learning with Experts
    Anders AamandJustin Y. ChenHuy Lê Nguyễn, and Sandeep Silwal
    ACDA 2023
    Accepted as poster. Independent and concurrent work resolves this problem.
  6. Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds
    SODA 2023
    Merge of two independent and concurrent works by Chen, Narayanan, and Xu and by Ghazi, Kumar, Manurangsi, and Nelson.

2022

  1. (Optimal) Online Bipartite Matching with Degree Information
    Anders AamandJustin Y. Chen, and Piotr Indyk
    NeurIPS 2022
  2. Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
    NeurIPS 2022
  3. Streaming Algorithms for Support-Aware Histograms
    Justin Y. ChenPiotr Indyk, and Tal Wagner
    ICML 2022
  4. Faster Fundamental Graph Algorithms via Learned Predictions
    Justin Y. ChenSandeep SilwalAli Vakilian, and Fred Zhang
    ICML 2022
  5. Triangle and Four Cycle Counting with Predictions in Graph Streams
    ICLR 2022
    Merge of independent and concurrent works by Chen, Eden, Indyk, Narayanan, Rubinfeld, Silwal and Wagner and by Lin, Woodruff, and Zhang.

2020

  1. Worst-Case Analysis for Randomly Collected Data
    Justin Y. ChenGregory Valiant , and Paul Valiant
    NeurIPS 2020 (Oral Award)

2019

  1. CrossTrainer: Practical Domain Adaptation with Loss Reweighting
    Justin Chen*Edward GanKexin RongSahaana Suri, and Peter Bailis
    SIGMOD DEEM 2019

2017

  1. Impact of MODIS sensor calibration updates on Greenland Ice Sheet surface reflectance and albedo trends
    Kimberly A. Casey* , Chris M. Polashenski , Justin Chen, and Mark Tedesco
    The Cryosphere 2017

2015

  1. Neither dust nor black carbon causing apparent albedo decline in Greenland’s dry snow zone: Implications for MODIS C5 surface reflectance
    Chris Polashenski* , Jack E. Dibb , Mark G. Flanner , Justin Y. Chen, Zoe R. Courville , Alexandra M. Lai , James J. Schauer , Martin M. Shafer , and Mark Bergin
    Geophysical Research Letters 2015

2014

  1. Observations of pronounced Greenland ice sheet firn warming and implications for runoff production
    Chris Polashenski* , Zoe Courville , Carl Benson , Anna Wagner , Justin Chen, Gifford Wong , Robert Hawley , and Dorothy Hall
    Geophysical Research Letters 2014