activity
20192026
most citedOptimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method

3 citations · 3 across the 5 of their papers we have counts for

collaborators

10 papers

math.OC2026

Anchored Spectral Estimator for Rigid Motion Synchronization

Ziyue Zhao, Huikang Liu, Man-Chung Yue

A rigid motion in consists of a proper rotation and a translation, and it can be represented as a matrix in . The problem of rigid mo…

math.OC2023

On the Estimation Performance of Generalized Power Method for Heteroscedastic Probabilistic PCA

Jinxin Wang, Chonghe Jiang, Huikang Liu +1

The heteroscedastic probabilistic principal component analysis (PCA) technique, a variant of the classic PCA that considers data heterogeneity, is receiving more and more attention…

math.OC2023

ReSync: Riemannian Subgradient-based Robust Rotation Synchronization

Huikang Liu, Xiao Li, Anthony Man-Cho So

This work presents ReSync, a Riemannian subgradient-based algorithm for solving the robust rotation synchronization problem, which arises in various engineering applications. ReSyn…

cs.CR2023

Differential Privacy via Distributionally Robust Optimization

Aras Selvi, Huikang Liu, Wolfram Wiesemann

In recent years, differential privacy has emerged as the de facto standard for sharing statistics of datasets while limiting the disclosure of private information about the involve…

cs.CG2023

A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data

Jiajin Li, Jianheng Tang, Lemin Kong +4

In this work, we present the Bregman Alternating Projected Gradient (BAPG) method, a single-loop algorithm that offers an approximate solution to the Gromov-Wasserstein (GW) distan…

math.OC2022

A Communication-Efficient Decentralized Newton's Method with Provably Faster Convergence

Huikang Liu, Jiaojiao Zhang, Anthony Man-Cho So +1

In this paper, we consider a strongly convex finite-sum minimization problem over a decentralized network and propose a communication-efficient decentralized Newton's method for so…