6 papers
Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis
Yang Jiao, Kai Yang, Dongjin Song
Distributionally Robust Optimization (DRO), which aims to find an optimal decision that minimizes the worst case cost over the ambiguity set of probability distribution, has been w…
Anomaly Detection in Event-triggered Traffic Time Series via Similarity Learning
Shaoyu Dou, Kai Yang, Yang Jiao +2
Time series analysis has achieved great success in cyber security such as intrusion detection and device identification. Learning similarities among multiple time series is a cruci…
PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization
Yang Jiao, Xiaodong Wang, Kai Yang
Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of applications, e.g., medical question-answering, mathematical sciences, and code generat…
Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning
Hui Ma, Kai Yang, Yang Jiao
Network traffic prediction plays a crucial role in intelligent network operation. Traditional prediction methods often rely on centralized training, necessitating the transfer of v…
Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence
Yang Jiao, Kai Yang, Chengtao Jian
Trilevel learning (TLL) found diverse applications in numerous machine learning applications, ranging from robust hyperparameter optimization to domain adaptation. However, existin…
Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
Chengtao Jian, Kai Yang, Yang Jiao
Out-of-Distribution (OOD) generalization in machine learning is a burgeoning area of study. Its primary goal is to enhance the adaptability and resilience of machine learning model…