Jun-Ting Hsieh

According to our database, Jun-Ting Hsieh authored at least 29 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2026

Explicit Constant-Alphabet Subspace Design Codes.

Rohan Goyal, Venkatesan Guruswami, Jun-Ting Hsieh

CoRR, April, 2026

Explicit Almost-Optimal ϵ-Balanced Codes via Free Expander Walks.

Jun-Ting Hsieh, Sidhanth Mohanty, Rachel Yun Zhang

CoRR, January, 2026

Rigorous Implications of the Low-Degree Heuristic.

Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel

CoRR, January, 2026

Certifying Euclidean Sections and Finding Planted Sparse Vectors Beyond the \(\boldsymbol{\sqrt {n}}\) Dimension Threshold.

Venkatesan Guruswami, Jun-Ting Hsieh, Prasad Raghavendra

SIAM J. Comput., 2026

Sparsifying Cayley Graphs on Every Group.

Jun-Ting Hsieh, Daniel Z. Lee, Sidhanth Mohanty, Aaron Putterman, Rachel Yun Zhang

Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms, 2026

Coloring 3-Colorable Graphs with Low Threshold Rank.

Jun-Ting Hsieh

Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms, 2026

2025

Solving Random Planted CSPs below the n^k/2} Threshold.

Arpon Basu, Jun-Ting Hsieh, Andrew D. Lin, Peter Manohar

CoRR, July, 2025

Explicit Two-Sided Vertex Expanders beyond the Spectral Barrier.

Jun-Ting Hsieh, Ting-Chun Lin, Sidhanth Mohanty, Ryan O'Donnell, Rachel Yun Zhang

Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 2025

Rounding Large Independent Sets on Expanders.

Mitali Bafna, Jun-Ting Hsieh, Pravesh K. Kothari

Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 2025

Explicit Lossless Vertex Expanders.

Jun-Ting Hsieh, Alexander Lubotzky, Sidhanth Mohanty, Assaf Reiner, Rachel Yun Zhang

Proceedings of the 66th IEEE Annual Symposium on Foundations of Computer Science, 2025

The Quasi-Polynomial Low-Degree Conjecture is False.

Rares-Darius Buhai, Jun-Ting Hsieh, Aayush Jain, Pravesh K. Kothari

Proceedings of the 66th IEEE Annual Symposium on Foundations of Computer Science, 2025

Improved Lower Bounds for all Odd-Query Locally Decodable Codes.

Arpon Basu, Jun-Ting Hsieh, Pravesh K. Kothari, Andrew D. Lin

Proceedings of the 66th IEEE Annual Symposium on Foundations of Computer Science, 2025

Predicting quantum channels over general product distributions.

Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh, Hsin-Yuan Huang, Jane Lange, Jerry Li

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Small Even Covers, Locally Decodable Codes and Restricted Subgraphs of Edge-Colored Kikuchi Graphs.

Jun-Ting Hsieh, Pravesh K. Kothari, Sidhanth Mohanty, David Munhá Correia, Benny Sudakov

CoRR, 2024

Explicit Two-Sided Unique-Neighbor Expanders.

Jun-Ting Hsieh, Theo McKenzie, Sidhanth Mohanty, Pedro Paredes

Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024

New SDP Roundings and Certifiable Approximation for Cubic Optimization.

Jun-Ting Hsieh, Pravesh K. Kothari, Lucas Pesenti, Luca Trevisan

Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

Certifying Euclidean Sections and Finding Planted Sparse Vectors Beyond the √n Dimension Threshold.

Venkatesan Guruswami, Jun-Ting Hsieh, Prasad Raghavendra

Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

2023

A simple and sharper proof of the hypergraph Moore bound.

Jun-Ting Hsieh, Pravesh K. Kothari, Sidhanth Mohanty

Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Ellipsoid Fitting up to a Constant.

Jun-Ting Hsieh, Pravesh K. Kothari, Aaron Potechin, Jeff Xu

Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Approximating Max-Cut on Bounded Degree Graphs: Tighter Analysis of the FKL Algorithm.

Jun-Ting Hsieh, Pravesh K. Kothari

Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Efficient Algorithms for Semirandom Planted CSPs at the Refutation Threshold.

Venkatesan Guruswami, Jun-Ting Hsieh, Pravesh K. Kothari, Peter Manohar

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

2022

Algorithmic Thresholds for Refuting Random Polynomial Systems.

Jun-Ting Hsieh, Pravesh K. Kothari

Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

Polynomial-Time Power-Sum Decomposition of Polynomials.

Mitali Bafna, Jun-Ting Hsieh, Pravesh K. Kothari, Jeff Xu

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Certifying Solution Geometry in Random CSPs: Counts, Clusters and Balance.

Jun-Ting Hsieh, Sidhanth Mohanty, Jeff Xu

Proceedings of the 37th Computational Complexity Conference, 2022

2019

Learning Neural PDE Solvers with Convergence Guarantees.

Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann, Lucia Mirabella, Stefano Ermon

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Vision-Based Gait Analysis for Senior Care.

David Xue, Anin Sayana, Evan Darke, Kelly Shen, Jun-Ting Hsieh, Zelun Luo, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei

CoRR, 2018

Learning to Decompose and Disentangle Representations for Video Prediction.

Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, Juan Carlos Niebles

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Graph Distillation for Action Detection with Privileged Modalities.

Zelun Luo, Jun-Ting Hsieh, Lu Jiang, Juan Carlos Niebles, Li Fei-Fei

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Graph Distillation for Action Detection with Privileged Information.

Zelun Luo, Lu Jiang, Jun-Ting Hsieh, Juan Carlos Niebles, Li Fei-Fei

CoRR, 2017