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…
Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives
Yiyuan Yang, Zheshun Wu, Yong Chu +3
Process mining, as a high-level field in data mining, plays a crucial role in enhancing operational efficiency and decision-making across organizations. In this survey paper, we de…
On the Necessity of Collaboration for Online Model Selection with Decentralized Data
Junfan Li, Zheshun Wu, Zenglin Xu +1
We consider online model selection with decentralized data over clients, and study the necessity of collaboration among clients. Previous work proposed various federated algori…
Topology Learning for Heterogeneous Decentralized Federated Learning over Unreliable D2D Networks
Zheshun Wu, Zenglin Xu, Dun Zeng +2
With the proliferation of intelligent mobile devices in wireless device-to-device (D2D) networks, decentralized federated learning (DFL) has attracted significant interest. Compare…
Information-Theoretic Generalization Analysis for Topology-aware Heterogeneous Federated Edge Learning over Noisy Channels
Zheshun Wu, Zenglin Xu, Hongfang Yu +1
With the rapid growth of edge intelligence, the deployment of federated learning (FL) over wireless networks has garnered increasing attention, which is called Federated Edge Learn…
Advocating for the Silent: Enhancing Federated Generalization for Non-Participating Clients
Zheshun Wu, Zenglin Xu, Dun Zeng +2
Federated Learning (FL) has surged in prominence due to its capability of collaborative model training without direct data sharing. However, the vast disparity in local data distri…