10 citations · 36 across the 11 of their papers we have counts for
11 papers
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…
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…
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…
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…
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…
CPMLHO:Hyperparameter Tuning via Cutting Plane and Mixed-Level Optimization
Shuo Yang, Yang Jiao, Shaoyu Dou +2
The hyperparameter optimization of neural network can be expressed as a bilevel optimization problem. The bilevel optimization is used to automatically update the hyperparameter, a…
Asynchronous Distributed Bilevel Optimization
Yang Jiao, Kai Yang, Tiancheng Wu +2
Bilevel optimization plays an essential role in many machine learning tasks, ranging from hyperparameter optimization to meta-learning. Existing studies on bilevel optimization, ho…
Distributed Distributionally Robust Optimization with Non-Convex Objectives
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…
Task-aware Similarity Learning for Event-triggered Time Series
Shaoyu Dou, Kai Yang, Yang Jiao +2
Time series analysis has achieved great success in diverse applications such as network security, environmental monitoring, and medical informatics. Learning similarities among dif…
TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series
Yang Jiao, Kai Yang, Shaoyu Dou +3
Multivariate time series (MTS) data are becoming increasingly ubiquitous in diverse domains, e.g., IoT systems, health informatics, and 5G networks. To obtain an effective represen…