6 citations · 8 across the 17 of their papers we have counts for
19 papers
A Unified Variational Design of Predictive Mirror Descent in Convex Games under Stochastic Feedback
Yunian Pan, Tao Li, Quanyan Zhu
Mirror descent provides a geometric framework for learning in games, but its last-iterate behavior can fail in weakly stable regimes, where the dynamics may exhibit rotational or r…
Bayesian Holonic Systems: Equilibrium, Uniqueness, and Computation
Yunian Pan, Quanyan Zhu
This paper addresses the challenge of modeling and control in hierarchical, multi-agent systems, known as holonic systems, where local agent decisions are coupled with global syste…
Timing-Aware Two-Player Stochastic Games with Self-Triggered Control
Yunian Pan, Quanyan Zhu
We study self-triggered two-player stochastic games on Piecewise Deterministic Markov Processes (PDMPs) where each agent decides when to observe and which open-loop action to hold.…
Decentralized No-Regret Frequency-Time Scheduling for FMCW Radar Interference Avoidance
Yunian Pan, Jun Li, Lifan Xu +2
Automotive FMCW radars are indispensable to modern ADAS and autonomous-driving systems, but their increasing density has intensified the risk of mutual interference. Existing mitig…
A Games-in-Games Paradigm for Strategic Hybrid Jump-Diffusions: Hamilton-Jacobi-Isaacs Hierarchy and Spectral Structure
Yunian Pan, Quanyan Zhu
This paper develops a hierarchical games-in-games control architecture for hybrid stochastic systems governed by regime-switching jump-diffusions. We model the interplay between co…
From Texts to Shields: Convergence of Large Language Models and Cybersecurity
Tao Li, Ya-Ting Yang, Yunian Pan +1
This report explores the convergence of large language models (LLMs) and cybersecurity, synthesizing interdisciplinary insights from network security, artificial intelligence, form…
Preference-Centric Route Recommendation: Equilibrium, Learning, and Provable Efficiency
Ya-Ting Yang, Yunian Pan, Quanyan Zhu
Traditional approaches to modeling and predicting traffic behavior often rely on Wardrop Equilibrium (WE), assuming non-atomic traffic demand and neglecting correlations in individ…
A Game-Theoretic Approach for High-Resolution Automotive FMCW Radar Interference Avoidance
Yunian Pan, Jun Li, Lifan Xu +2
Nonlinear frequency hopping has emerged as a promising approach for mitigating interference and enhancing range resolution in automotive FMCW radar systems. Achieving an optimal ba…
Model-Agnostic Meta-Policy Optimization via Zeroth-Order Estimation: A Linear Quadratic Regulator Perspective
Yunian Pan, Tao Li, Quanyan Zhu
Meta-learning has been proposed as a promising machine learning topic in recent years, with important applications to image classification, robotics, computer games, and control sy…
Meta Stackelberg Game: Robust Federated Learning against Adaptive and Mixed Poisoning Attacks
Tao Li, Henger Li, Yunian Pan +3
Federated learning (FL) is susceptible to a range of security threats. Although various defense mechanisms have been proposed, they are typically non-adaptive and tailored to speci…
Model-Agnostic Zeroth-Order Policy Optimization for Meta-Learning of Ergodic Linear Quadratic Regulators
Yunian Pan, Quanyan Zhu
Meta-learning has been proposed as a promising machine learning topic in recent years, with important applications to image classification, robotics, computer games, and control sy…
On the Variational Interpretation of Mirror Play in Monotone Games
Yunian Pan, Tao Li, Quanyan Zhu
Mirror play (MP) is a well-accepted primal-dual multi-agent learning algorithm where all agents simultaneously implement mirror descent in a distributed fashion. The advantage of M…
Decision-Dominant Strategic Defense Against Lateral Movement for 5G Zero-Trust Multi-Domain Networks
Tao Li, Yunian Pan, Quanyan Zhu
Multi-domain warfare is a military doctrine that leverages capabilities from different domains, including air, land, sea, space, and cyberspace, to create a highly interconnected b…
A First Order Meta Stackelberg Method for Robust Federated Learning
Yunian Pan, Tao Li, Henger Li +3
Previous research has shown that federated learning (FL) systems are exposed to an array of security risks. Despite the proposal of several defensive strategies, they tend to be no…
A First Order Meta Stackelberg Method for Robust Federated Learning (Technical Report)
Henger Li, Tianyi Xu, Tao Li +3
Recent research efforts indicate that federated learning (FL) systems are vulnerable to a variety of security breaches. While numerous defense strategies have been suggested, they…
Is Stochastic Mirror Descent Vulnerable to Adversarial Delay Attacks? A Traffic Assignment Resilience Study
Yunian Pan, Tao Li, Quanyan Zhu
\textit{Intelligent Navigation Systems} (INS) are exposed to an increasing number of informational attack vectors, which often intercept through the communication channels between…
On the Resilience of Traffic Networks under Non-Equilibrium Learning
Yunian Pan, Tao Li, Quanyan Zhu
We investigate the resilience of learning-based \textit{Intelligent Navigation Systems} (INS) to informational flow attacks, which exploit the vulnerabilities of IT infrastructure…
On Poisoned Wardrop Equilibrium in Congestion Games
Yunian Pan, Quanyan Zhu
Recent years have witnessed a growing number of attack vectors against increasingly interconnected traffic networks. Informational attacks have emerged as the prominent ones that a…
Efficient Episodic Learning of Nonstationary and Unknown Zero-Sum Games Using Expert Game Ensembles
Yunian Pan, Quanyan Zhu
Game theory provides essential analysis in many applications of strategic interactions. However, the question of how to construct a game model and what is its fidelity is seldom ad…