2 citations · 4 across the 11 of their papers we have counts for
11 papers
From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining
Yiyuan Yang, Zheshun Wu, Yong Chu +3
Process mining has long turned event logs into process knowledge: discovered models, conformance evidence, bottleneck diagnoses, and runtime predictions. Agentic AI changes the tar…
A Unified Algorithmic Framework for Hybrid Reinforcement Learning in Tabular MDPs with Shifted Transition Dynamics
Zheshun Wu, Renjie Zheng, Jinhang Zuo +2
This paper investigates a hybrid reinforcement learning setting in tabular Markov Decision Processes (MDPs), where an agent aims to learn an optimal policy by combining online inte…
CANS: Accelerating Multiuser Collaborative Edge Inference via Cooperative Autodidactic NeuroSurgeon
Zheshun Wu, Ziyang Zhang, Changyao Lin +2
Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering intelligent services to resource-…
SparseDVFS: Sparse-Aware DVFS for Energy-Efficient Edge Inference
Ziyang Zhang, Zheshun Wu, Jie Liu +1
Deploying deep neural networks (DNNs) on power-sensitive edge devices presents a formidable challenge. While Dynamic Voltage and Frequency Scaling (DVFS) is widely employed for ene…
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization
Dun Zeng, Zheshun Wu, Shiyu Liu +3
Federated Learning (FL) is a distributed learning approach that trains machine learning models across multiple devices while keeping their local data private. However, FL often fac…
Online Optimization for Learning to Communicate over Time-Correlated Channels
Zheshun Wu, Junfan Li, Zenglin Xu +2
Machine learning techniques have garnered great interest in designing communication systems owing to their capacity in tackling with channel uncertainty. To provide theoretical gua…