Ya‐Feng Liu

Proximal-Based Generative Modeling for Bayesian Inverse Problems

Boyang Zhang, Zhiguo Wang, Ya‐Feng Liu

Score-based diffusion models demonstrate superior performance in generative tasks but encounter fundamental bottlenecks in inverse problems due to the analytical intractability of the time-dependent likelihood score. To bridge this gap, we propose a novel proximal-based generative modeling (PGM) framework that rigorously circumvents …

Proximal-Based Generative Modeling for Bayesian Inverse Problems

Boyang Zhang, Zhiguo Wang, Ya‐Feng Liu

Score-based diffusion models demonstrate superior performance in generative tasks but encounter fundamental bottlenecks in inverse problems due to the analytical intractability of the time-dependent likelihood score. To bridge this gap, we propose a novel proximal-based generative modeling (PGM) framework that rigorously circumvents …

Byzantine-Robust Distributed SGD: A Unified Analysis and Tight Error Bounds

Boyuan Ruan, Xiaoyu Wang, Ya‐Feng Liu

Byzantine-robust distributed optimization relies on robust aggregation rules to mitigate the influence of malicious Byzantine workers. Despite the proliferation of such rules, a unified convergence analysis framework that accommodates general data heterogeneity is lacking. In this work, we provide a thorough convergence …

Byzantine-Robust Distributed SGD: A Unified Analysis and Tight Error Bounds

Boyuan Ruan, Xiaoyu Wang, Ya‐Feng Liu

Byzantine-robust distributed optimization relies on robust aggregation rules to mitigate the influence of malicious Byzantine workers. Despite the proliferation of such rules, a unified convergence analysis framework that accommodates general data heterogeneity is lacking. In this work, we provide a thorough convergence …

Asymptotic Analysis of Nonlinear One-Bit Precoding in Massive MIMO Systems via Approximate Message Passing

Zheyu Wu, Junjie Ma, Ya‐Feng Liu, Bruno Clerckx

Massive multiple-input multiple-output (MIMO) systems employing one-bit digital-to-analog converters offer a hardware-efficient solution for wireless communications. However, the one-bit constraint poses significant challenges for precoding design, as it transforms the problem into a discrete and nonconvex optimization task. In this paper, we …

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A Riemannian Alternating Descent Ascent Algorithmic Framework for Nonconvex-Linear Minimax Problems on Riemannian Manifolds

Meng Xu, Bo Jiang, Ya‐Feng Liu, Anthony Man–Cho So

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 this class of problems, we develop a flexible Riemannian alternating descent ascent (RADA) algorithmic framework. Within …

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A Unified Distributed Algorithm for Hybrid Near-Far Field Activity Detection in Cell-Free Massive MIMO

Jingreng Lei, Yang Li, Ziyue Wang, Qingfeng Lin et autres

A great amount of endeavor has recently been devoted to activity detection for massive machine-type communications in cell-free multiple-input multiple-output (MIMO) systems. However, as the number of antennas at the access points (APs) increases, the Rayleigh distance that separates the near-field and …

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Blocking PCSK9 suppresses hepatocellular carcinoma immune escape by decreasing FLI1-mediated SPP1 and PD-L1 expression

Changpeng� Hu, Ming Qin, Wenjing Lai, Huyue Zhou et autres

Background Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a newly identified immunosuppressive regulator, but its mechanism of suppressing antitumor immunity remains ambiguous. This study aims to uncover the underlying mechanism by which PCSK9 promotes hepatocellular carcinoma (HCC) immune escape and to explore …

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Covariance-Based Device Activity Detection With Massive MIMO for Near-Field Correlated Channels

Ziyue Wang, Yang Li, Ya‐Feng Liu, Junjie Ma

This paper studies the device activity detection problem in a massive multiple-input multiple-output (MIMO) system for near-field communications (NFC). In this system, active devices transmit their signature sequences to the base station (BS), which detects the active devices based on the received …

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QoS-Aware and Routing-Flexible Network Slicing for Service-Oriented Networks

Wei‐Kun Chen, Ya‐Feng Liu, Yu‐Hong Dai, Zhi-Quan Tom Luo

In this paper, we consider the network slicing () problem which aims to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and manage network resources to meet diverse quality of service (QoS) requirements. We propose …

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Joint Design of Radar Receive Filter and Unimodular ISAC Waveform With Sidelobe Level Control

Kecheng Zhang, Ya‐Feng Liu, Zhongbin Wang, Weijie Yuan et autres

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square …

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An Inexact Proximal Framework for Nonsmooth Riemannian Difference-of-Convex Optimization

Bo Jiang, Meng Xu, Xingju Cai, Ya‐Feng Liu

Nonsmooth Riemannian optimization has attracted increasing attention, especially in problems with sparse structures. While existing formulations typically involve convex nonsmooth terms, incorporating nonsmooth difference-of-convex (DC) penalties can enhance recovery accuracy. In this paper, we study a class of nonsmooth Riemannian optimization problems …