Jun-Ting Hsieh

According to our database, Jun-Ting Hsieh authored at least 15 papers between 2017 and 2024.

Collaborative distances:

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

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

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

2023

Explicit two-sided unique-neighbor expanders.

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

CoRR, 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