On capacity of optical channels with coherent detection. - Hye Won Chung; Saikat Guha 001; Lizhong Zheng (ISIT, 2011)

Superadditivity of quantum channel coding rate with finite blocklength quantum measurements. - Hye Won Chung; Lizhong Zheng (Allerton, 2013)

Superadditivity of quantum channel coding rate with finite blocklength quantum measurements. - Hye Won Chung; Saikat Guha 001; Lizhong Zheng (ISIT, 2014)

Extracting classical information from quantum states: fundamental limits, adaptive and finite-length measurements. - Hye Won Chung (2014)

Bounds on variance for symmetric unimodal distributions. - Hye Won Chung; Brian M. Sadler; Alfred O. Hero III (Allerton, 2015)

Unequal error protection coding approaches to the noisy 20 questions problem. - Hye Won Chung; Lizhong Zheng; Brian M. Sadler; Alfred O. Hero III (ISIT, 2016)

On capacity of optical communications over a lossy bosonic channel with a receiver employing the most general coherent electro-optic feedback control. - Hye Won Chung; Saikat Guha 001; Lizhong Zheng (CoRR, 2016)

Superadditivity of Quantum Channel Coding Rate With Finite Blocklength Joint Measurements. - Hye Won Chung; Saikat Guha 001; Lizhong Zheng (IEEE Trans. Inf. Theory, 2016)

Bounds on Variance for Unimodal Distributions. - Hye Won Chung; Brian M. Sadler; Alfred O. Hero III (IEEE Trans. Inf. Theory, 2017)

Trade-offs Between Query Difficulty and Sample Complexity in Crowdsourced Data Acquisition. - Hye Won Chung; Ji Oon Lee; Doyeon Kim; Alfred O. Hero III (Allerton, 2018)

Fundamental Limits on Data Acquisition: Trade-offs Between Sample Complexity and Query Difficulty. - Hye Won Chung; Ji Oon Lee; Alfred O. Hero III (ISIT, 2018)

Parity Crowdsourcing for Cooperative Labeling. - Hye Won Chung; Ji Oon Lee; Doyeon Kim; Alfred O. Hero III (CoRR, 2018)

Unequal Error Protection Querying Policies for the Noisy 20 Questions Problem. - Hye Won Chung; Brian M. Sadler; Lizhong Zheng; Alfred O. Hero III (IEEE Trans. Inf. Theory, 2018)

Weak Detection of Signal in the Spiked Wigner Model. - Hye Won Chung; Ji Oon Lee (ICML, 2019)

Shallow Neural Network can Perfectly Classify an Object following Separable Probability Distribution. - Youngjae Min; Hye Won Chung (ISIT, 2019)

Crowdsourced Classification with XOR Queries: An Algorithm with Optimal Sample Complexity. - Daesung Kim; Hye Won Chung (ISIT, 2020)

Weak Detection in the Spiked Wigner Model with General Rank. - Ji Hyung Jung; Hye Won Chung; Ji Oon Lee (CoRR, 2020)

Crowdsourced Classification with XOR Queries: Fundamental Limits and An Efficient Algorithm. - Daesung Kim; Hye Won Chung (CoRR, 2020)

Hypergraph Clustering in the Weighted Stochastic Block Model via Convex Relaxation of Truncated MLE. - Jeonghwan Lee; Daesung Kim; Hye Won Chung (CoRR, 2020)

Crowdsourced Labeling for Worker-Task Specialization Block Model. - Doyeon Kim; Hye Won Chung (CoRR, 2020)

Robust Hypergraph Clustering via Convex Relaxation of Truncated MLE. - Jeonghwan Lee; Daesung Kim; Hye Won Chung (IEEE J. Sel. Areas Inf. Theory, 2020)

Detection of Signal in the Spiked Rectangular Models. - Ji Hyung Jung; Hye Won Chung; Ji Oon Lee (ICML, 2021)

Crowdsourced Labeling for Worker-Task Specialization Model. - Doyeon Kim; Hye Won Chung (ISIT, 2021)

Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks. - Jinhee Lee; Haeri Kim; Youngkyu Hong; Hye Won Chung (NeurIPS, 2021)

Binary Classification With XOR Queries: Fundamental Limits and an Efficient Algorithm. - Daesung Kim; Hye Won Chung (IEEE Trans. Inf. Theory, 2021)

A Generalized Worker-Task Specialization Model for Crowdsourcing: Optimal Limits and Algorithm. - Doyeon Kim; Jeonghwan Lee; Hye Won Chung (ISIT, 2022)

Weak Detection in the Spiked Wigner Model. - Hye Won Chung; Ji Oon Lee (IEEE Trans. Inf. Theory, 2022)

Graph Matching in Correlated Stochastic Block Models for Improved Graph Clustering. - Joonhyuk Yang; Hye Won Chung (Allerton, 2023)

Test-Time Adaptation via Self-Training with Nearest Neighbor Information. - Minguk Jang; Sae-Young Chung; Hye Won Chung (ICLR, 2023)

Data Valuation Without Training of a Model. - Nohyun Ki; Hoyong Choi; Hye Won Chung (ICLR, 2023)

Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing. - Hyeonsu Jeong; Hye Won Chung (ICML, 2023)

Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation. - Joonhyuk Yang; Dongpil Shin; Hye Won Chung (ICML, 2023)

Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization. - Daesung Kim; Hye Won Chung (NeurIPS, 2023)

Detection problems in the spiked matrix models. - Ji Hyung Jung; Hye Won Chung; Ji Oon Lee (CoRR, 2023)

BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges. - Hoyong Choi; Nohyun Ki; Hye Won Chung (ICML, 2024)

SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching. - Yongmin Lee; Hye Won Chung (ICML, 2024)

Exact Graph Matching in Correlated Gaussian-Attributed Erdős- Rényi Mode. - Joonhyuk Yang; Hye Won Chung (ISIT, 2024)

Understanding Self-Distillation and Partial Label Learning in Multi-Class Classification with Label Noise. - Hyeonsu Jeong; Hye Won Chung (CoRR, 2024)

Exact Graph Matching in Correlated Gaussian-Attributed Erdös-Rényi Model. - Joonhyuk Yang; Hye Won Chung (CoRR, 2024)

A Worker-Task Specialization Model for Crowdsourcing: Efficient Inference and Fundamental Limits. - Doyeon Kim; Jeonghwan Lee; Hye Won Chung (IEEE Trans. Inf. Theory, 2024)

Representation Norm Amplification for Out-of-Distribution Detection in Long-Tail Learning. - Dong Geun Shin; Hye Won Chung (Trans. Mach. Learn. Res., 2024)

Detection Problems in the Spiked Random Matrix Models. - Ji Hyung Jung; Hye Won Chung; Ji Oon Lee (IEEE Trans. Inf. Theory, 2024)

Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels. - Hyeonsu Jeong; Hye Won Chung (ICLR, 2025)

Label Distribution Shift-Aware Prediction Refinement for Test-Time Adaptation. - Minguk Jang; Hye Won Chung (Trans. Mach. Learn. Res., 2025)

Exact Matching in Correlated Networks with Node Attributes for Improved Community Recovery. - Joonhyuk Yang; Hye Won Chung (CoRR, 2025)