Justin Y. Chen

43 papers A* 17A 1Journal 24Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	On the Structure of Replicable Hypothesis Testers. SODA Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Shyam Narayanan, Sandeep Silwal
2026	J	`jnl`	Skirting Additive Error Barriers for Private Turnstile Streams. CoRR Anders Aamand, Justin Y. Chen, Sandeep Silwal
2025	J	`jnl`	Breaking the n CoRR Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2025	A*	`conf`	Breaking the n1.5 Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition. ICML Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2025	J	`jnl`	Hypothesis Selection: A High Probability Conundrum. CoRR Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Sandeep Silwal
2025	A*	`conf`	Improved Approximations for Hard Graph Problems using Predictions. ICML Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	J	`jnl`	Improved Approximations for Hard Graph Problems using Predictions. CoRR Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	A*	`conf`	Learning-Augmented Frequent Directions. ICLR Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	J	`jnl`	Learning-Augmented Frequent Directions. CoRR Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu
2025	J	`jnl`	On the Structure of Replicable Hypothesis Testers. CoRR Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Shyam Narayanan, Sandeep Silwal
2025	J	`jnl`	Private Text Generation by Seeding Large Language Model Prompts. CoRR Supriya Nagesh, Justin Y. Chen, Nina Mishra, Tal Wagner
2025	A*	`conf`	Scalable Private Partition Selection via Adaptive Weighting. ICML Justin Y. Chen, Vincent Cohen-Addad, Alessandro Epasto, Morteza Zadimoghaddam
2025	J	`jnl`	Scalable Private Partition Selection via Adaptive Weighting. CoRR Justin Y. Chen, Vincent Cohen-Addad, Alessandro Epasto, Morteza Zadimoghaddam
2024	J	`jnl`	Differentially Private Gomory-Hu Trees. CoRR Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2024	A*	`conf`	Evaluating the World Model Implicit in a Generative Model. NeurIPS Keyon Vafa, Justin Y. Chen, Ashesh Rambachan, Jon M. Kleinberg, Sendhil Mullainathan
2024	J	`jnl`	Evaluating the World Model Implicit in a Generative Model. CoRR Keyon Vafa, Justin Y. Chen, Jon M. Kleinberg, Sendhil Mullainathan, Ashesh Rambachan
2024	A	`conf`	Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. ITCS Justin Y. Chen, Piotr Indyk, David P. Woodruff
2024	A*	`conf`	Statistical-Computational Trade-offs for Density Estimation. NeurIPS Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu
2024	J	`jnl`	Statistical-Computational Trade-offs for Density Estimation. CoRR Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu
2023	A*	`conf`	Constant Approximation for Individual Preference Stable Clustering. NeurIPS Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
2023	J	`jnl`	Constant Approximation for Individual Preference Stable Clustering. CoRR Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
2023	A*	`conf`	Data Structures for Density Estimation. ICML Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
2023	J	`jnl`	Data Structures for Density Estimation. CoRR Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
2023	A*	`conf`	Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. SODA Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu
2023	A*	`conf`	Improved Frequency Estimation Algorithms with and without Predictions. NeurIPS Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
2023	J	`jnl`	Improved Frequency Estimation Algorithms with and without Predictions. CoRR Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian
2023	J	`jnl`	Improved Space Bounds for Learning with Experts. CoRR Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal
2023	—	`conf`	Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. ACDA Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
2023	J	`jnl`	Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. CoRR Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
2023	J	`jnl`	Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. CoRR Justin Y. Chen, Piotr Indyk, David P. Woodruff
2022	A*	`conf`	(Optimal) Online Bipartite Matching with Degree Information. NeurIPS Anders Aamand, Justin Y. Chen, Piotr Indyk
2022	J	`jnl`	All-Pairs Shortest Path Distances with Differential Privacy: Improved Algorithms for Bounded and Unbounded Weights. CoRR Justin Y. Chen, Shyam Narayanan, Yinzhan Xu
2022	A*	`conf`	Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. NeurIPS Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
2022	J	`jnl`	Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. CoRR Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
2022	A*	`conf`	Faster Fundamental Graph Algorithms via Learned Predictions. ICML Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
2022	J	`jnl`	Faster Fundamental Graph Algorithms via Learned Predictions. CoRR Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
2022	A*	`conf`	Streaming Algorithms for Support-Aware Histograms. ICML Justin Y. Chen, Piotr Indyk, Tal Wagner
2022	J	`jnl`	Streaming Algorithms for Support-Aware Histograms. CoRR Justin Y. Chen, Piotr Indyk, Tal Wagner
2022	A*	`conf`	Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
2022	J	`jnl`	Triangle and Four Cycle Counting with Predictions in Graph Streams. CoRR Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
2021	J	`jnl`	Online Bipartite Matching with Predicted Degrees. CoRR Justin Y. Chen, Piotr Indyk
2020	A*	`conf`	Worst-Case Analysis for Randomly Collected Data. NeurIPS Justin Y. Chen, Gregory Valiant, Paul Valiant
2019	J	`jnl`	How bad is worst-case data if you know where it comes from? CoRR Justin Y. Chen, Gregory Valiant, Paul Valiant