activity
20082025
most citedA Deep Reinforcement Learning-Based Framework for Content Caching

12 citations · 98 across the 61 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

eess.IV2019★ 9 cited

Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction

Yantao Lu, Yunhan Jia, Jianyu Wang +4

Neural networks are known to be vulnerable to carefully crafted adversarial examples, and these malicious samples often transfer, i.e., they remain adversarial even against other m…

cs.LG2019★ 5 cited

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…

cs.LG2019★ 6 cited

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…

cs.CV2019★ 1 cited

Autonomous Human Activity Classification from Ego-vision Camera and Accelerometer Data

Yantao Lu, Senem Velipasalar

There has been significant amount of research work on human activity classification relying either on Inertial Measurement Unit (IMU) data or data from static cameras providing a t…

cs.IT2019

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…

cs.LG2019★ 11 cited

Enhancing Cross-task Transferability of Adversarial Examples with Dispersion Reduction

Yunhan Jia, Yantao Lu, Senem Velipasalar +2

Neural networks are known to be vulnerable to carefully crafted adversarial examples, and these malicious samples often transfer, i.e., they maintain their effectiveness even again…

cs.IT2019

Power Control for Wireless VBR Video Streaming: From Optimization to Reinforcement Learning

Chuang Ye, M. Cenk Gursoy, Senem Velipasalar

In this paper, we investigate the problem of power control for streaming variable bit rate (VBR) videos over wireless links. A system model involving a transmitter (e.g., a base st…