Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks. - Jingqiu Ding; Samuel B. Hopkins 001; David Steurer (NeurIPS, 2020)

Robust recovery for stochastic block models. - Jingqiu Ding; Tommaso d'Orsi; Rajai Nasser; David Steurer (FOCS, 2021)

Fast algorithm for overcomplete order-3 tensor decomposition. - Jingqiu Ding; Tommaso d'Orsi; Chih-Hung Liu 001; David Steurer; Stefan Tiegel (COLT, 2022)

SQ Lower Bounds for Random Sparse Planted Vector Problem. - Jingqiu Ding; Yiding Hua (ALT, 2023)

Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions. - Yiding Hua; Jingqiu Ding; Tommaso d'Orsi; David Steurer (COLT, 2023)

Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression. - Rares-Darius Buhai; Jingqiu Ding; Stefan Tiegel (COLT, 2024)

Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust. - Hongjie Chen 004; Jingqiu Ding; Yiding Hua; David Steurer (NeurIPS, 2024)

Private Graphon Estimation via Sum-of-Squares. - Hongjie Chen 004; Jingqiu Ding; Tommaso d'Orsi; Yiding Hua; Chih-Hung Liu 001; David Steurer (STOC, 2024)

Low degree conjecture implies sharp computational thresholds in stochastic block model. - Jingqiu Ding; Yiding Hua; Lucas Slot; David Steurer (CoRR, 2025)

Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point. - Hongjie Chen 004; Jingqiu Ding; Yiding Hua; Stefan Tiegel (CoRR, 2025)