2 citations · 5 across the 16 of their papers we have counts for
17 papers
A Stochastic Riemannian Alternating Descent Ascent Method for Nonsmooth Composite Expectation Optimization on Riemannian Manifolds
Meng Xu, Bo Jiang, Ya-Feng Liu +1
In this paper, we consider a class of Riemannian nonsmooth composite expectation optimization problems, which arises in various machine learning, signal processing, and statistics…
An AMP-Based Asymptotic Analysis For Nonlinear One-Bit Precoding
Zheyu Wu, Junjie Ma, Ya-Feng Liu +1
This paper focuses on the asymptotic analysis of a class of nonlinear one-bit precoding schemes under Rayleigh fading channels. The considered scheme employs a convex-relaxation-th…
An Inexact Proximal Framework for Nonsmooth Riemannian Difference-of-Convex Optimization
Bo Jiang, Meng Xu, Xingju Cai +1
Nonsmooth Riemannian optimization has attracted increasing attention, especially in problems with sparse structures. While existing formulations typically involve convex nonsmooth…
Asymptotic Analysis of Nonlinear One-Bit Precoding in Massive MIMO Systems via Approximate Message Passing
Zheyu Wu, Junjie Ma, Ya-Feng Liu +1
Massive multiple-input multiple-output (MIMO) systems employing one-bit digital-to-analog converters offer a hardware-efficient solution for wireless communications. However, the o…
An Adaptive Proximal Inexact Gradient Framework and Its Application to Per-Antenna Constrained Joint Beamforming and Compression Design
Xilai Fan, Bo Jiang, Ya-Feng Liu
In this paper, we propose an adaptive proximal inexact gradient (APIG) framework for solving a class of nonsmooth composite optimization problems involving function and gradient er…
A New Adaptive Balanced Augmented Lagrangian Method with Application to ISAC Beamforming Design
Jiageng Wu, Bo Jiang, Xinxin Li +2
In this paper, we consider a class of convex programming problems with linear equality constraints, which finds broad applications in machine learning and signal processing. We pro…
On the Oracle Complexity of a Riemannian Inexact Augmented Lagrangian Method for Riemannian Nonsmooth Composite Problems
Meng Xu, Bo Jiang, Ya-Feng Liu +1
In this paper, we establish for the first time the oracle complexity of a Riemannian inexact augmented Lagrangian (RiAL) method with the classical dual update for solving a class o…
A Riemannian Alternating Descent Ascent Algorithmic Framework for Nonconvex-Linear Minimax Problems on Riemannian Manifolds
Meng Xu, Bo Jiang, Ya-Feng Liu +1
In this paper, we consider a class of nonconvex-linear minimax problems on Riemannian manifolds, which find wide applications in machine learning and signal processing. For solving…
Asymptotic SEP Analysis and Optimization of Linear-Quantized Precoding in Massive MIMO Systems
Zheyu Wu, Junjie Ma, Ya-Feng Liu +1
A promising approach to deal with the high hardware cost and energy consumption of massive MIMO transmitters is to use low-resolution digital-to-analog converters (DACs) at each an…
Linear One-Bit Precoding in Massive MIMO: Asymptotic SEP Analysis and Optimization
Zheyu Wu, Junjie Ma, Ya-Feng Liu +1
This paper focuses on the analysis and optimization of a class of linear one-bit precoding schemes for a downlink massive MIMO system under Rayleigh fading channels. The considered…
A Riemannian exponential augmented Lagrangian method for computing the projection robust Wasserstein distance
Bo Jiang, Ya-Feng Liu
Projecting the distance measures onto a low-dimensional space is an efficient way of mitigating the curse of dimensionality in the classical Wasserstein distance using optimal tran…
An Efficient Alternating Riemannian/Projected Gradient Descent Ascent Algorithm for Fair Principal Component Analysis
Meng Xu, Bo Jiang, Wenqiang Pu +2
Fair principal component analysis (FPCA), a ubiquitous dimensionality reduction technique in signal processing and machine learning, aims to find a low-dimensional representation f…
Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems
Zheyu Wu, Ya-Feng Liu, Bo Jiang +1
Quantized constant envelope (QCE) precoding, a new transmission scheme that only discrete QCE transmit signals are allowed at each antenna, has gained growing research interests du…
A Novel Negative Penalty Approach for Multiuser One-Bit Massive MIMO Downlink with PSK Signaling
Zheyu Wu, Bo Jiang, Ya-Feng Liu +1
This paper considers the one-bit precoding problem for the multiuser downlink massive multiple-input multiple-output (MIMO) system with phase shift keying (PSK) modulation and focu…
Antenna Efficiency in Massive MIMO Detection
Ruichen Jiang, Ya-Feng Liu
In this paper, we consider the multi-user detection problem in a multiple-input multiple-output (MIMO) system, where the number of receive antennas at the base station (BS) grows i…
Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection
Ruichen Jiang, Ya-Feng Liu, Chenglong Bao +1
The multiple-input multiple-output (MIMO) detection problem, a fundamental problem in modern digital communications, is to detect a vector of transmitted symbols from the noisy out…
-norm regularization algorithms for optimization over permutation matrices
Bo Jiang, Ya-Feng Liu, Zaiwen Wen
Optimization problems over permutation matrices appear widely in facility layout, chip design, scheduling, pattern recognition, computer vision, graph matching, etc. Since this pro…