12 citations · 12 across the 2 of their papers we have counts for
7 papers
Anomaly Detection via Controlled Sensing and Deep Active Inference
Geethu Joseph, Chen Zhong, M. Cenk Gursoy +2
In this paper, we address the anomaly detection problem where the objective is to find the anomalous processes among a given set of processes. To this end, the decision-making agen…
Deep Actor-Critic Reinforcement Learning for Anomaly Detection
Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
Anomaly detection is widely applied in a variety of domains, involving for instance, smart home systems, network traffic monitoring, IoT applications and sensor networks. In this p…
A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access
Chen Zhong, Ziyang Lu, M. Cenk Gursoy +1
To make efficient use of limited spectral resources, we in this work propose a deep actor-critic reinforcement learning based framework for dynamic multichannel access. We consider…
Deep Multi-Agent Reinforcement Learning Based Cooperative Edge Caching in Wireless Networks
Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
The growing demand on high-quality and low-latency multimedia services has led to much interest in edge caching techniques. Motivated by this, we in this paper consider edge cachin…
Actor-Critic Deep Reinforcement Learning for Dynamic Multichannel Access
Chen Zhong, Ziyang Lu, M. Cenk Gursoy +1
We consider the dynamic multichannel access problem, which can be formulated as a partially observable Markov decision process (POMDP). We first propose a model-free actor-critic d…
Learning-Based Delay-Aware Caching in Wireless D2D Caching Networks
Yi Li, Chen Zhong, M. Cenk Gursoy +1
Recently, wireless caching techniques have been studied to satisfy lower delay requirements and offload traffic from peak periods. By storing parts of the popular files at the mobi…