18 citations · 44 across the 16 of their papers we have counts for
16 papers
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…
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…
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…
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…
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…
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…
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
Peng Wang, Huikang Liu, Anthony Man-Cho So +1
The K-subspaces (KSS) method is a generalization of the K-means method for subspace clustering. In this work, we present local convergence analysis and a recovery guarantee for KSS…
Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Data
Jiajin Li, Jianheng Tang, Lemin Kong +4
In this paper, we study the design and analysis of a class of efficient algorithms for computing the Gromov-Wasserstein (GW) distance tailored to large-scale graph learning tasks.…
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part II
Jiaojiao Zhang, Huikang Liu, Anthony Man-Cho So +1
In Part I of this work, we have proposed a general framework of decentralized stochastic quasi-Newton methods, which converge linearly to the optimal solution under the assumption…
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I
Jiaojiao Zhang, Huikang Liu, Anthony Man-Cho So +1
In this work, we investigate stochastic quasi-Newton methods for minimizing a finite sum of cost functions over a decentralized network. In Part I, we develop a general algorithmic…
Linear Convergence of a Proximal Alternating Minimization Method with Extrapolation for -Norm Principal Component Analysis
Peng Wang, Huikang Liu, Anthony Man-Cho So
A popular robust alternative of the classic principal component analysis (PCA) is the -norm PCA (L1-PCA), which aims to find a subspace that captures the most variation in…
Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method
Peng Wang, Huikang Liu, Zirui Zhou +1
In this paper, we study the problem of exact community recovery in the symmetric stochastic block model, where a graph of vertices is randomly generated by partitioning the ver…
A Unified Approach to Synchronization Problems over Subgroups of the Orthogonal Group
Huikang Liu, Man-Chung Yue, Anthony Man-Cho So
The problem of synchronization over a group aims to estimate a collection of group elements based on noisy observations of a sub…
Is There Any Recovery Guarantee with Coupled Structured Matrix Factorization for Hyperspectral Super-Resolution?
Huikang Liu, Ruiyuan Wu, Wing-Kin Ma
Coupled structured matrix factorization (CoSMF) for hyperspectral super-resolution (HSR) has recently drawn significant interest in hyperspectral imaging for remote sensing. Presen…
On the Estimation Performance and Convergence Rate of the Generalized Power Method for Phase Synchronization
Huikang Liu, Man-Chung Yue, Anthony Man-Cho So
An estimation problem of fundamental interest is that of phase synchronization, in which the goal is to recover a collection of phases using noisy measurements of relative phases.…
Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods
Huikang Liu, Weijie Wu, Anthony Man-Cho So
A fundamental class of matrix optimization problems that arise in many areas of science and engineering is that of quadratic optimization with orthogonality constraints. Such probl…