90 citations · 227 across the 12 of their papers we have counts for
7 papers · 1 filter
A Generative Car-following Model Conditioned On Driving Styles
Yifan Zhang, Xinhong Chen, Jianping Wang +2
Car-following (CF) modeling, an essential component in simulating human CF behaviors, has attracted increasing research interest in the past decades. This paper pushes the state of…
Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center
Wenhong Tian, Minxian Xu, Guangyao Zhou +3
Load balancing is vital for the efficient and long-term operation of cloud data centers. With virtualization, post (reactive) migration of virtual machines after allocation is the…
BESS Aided Reconfigurable Energy Supply using Deep Reinforcement Learning for 5G and Beyond
Hao Yuan, Guoming Tang, Deke Guo +4
The year of 2020 has witnessed the unprecedented development of 5G networks, along with the widespread deployment of 5G base stations (BSs). Nevertheless, the enormous energy consu…
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization
Mostafa Pashazadeh, Kui Wu
Combinatorial optimization problems (COPs) on the graph with real-life applications are canonical challenges in Computer Science. The difficulty of finding quality labels for probl…
Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles
Jindi Zhang, Yang Lou, Jianping Wang +3
In recent years, many deep learning models have been adopted in autonomous driving. At the same time, these models introduce new vulnerabilities that may compromise the safety of a…
FedNILM: Applying Federated Learning to NILM Applications at the Edge
Yu Zhang, Guoming Tang, Qianyi Huang +3
Non-intrusive load monitoring (NILM) helps disaggregate the household's main electricity consumption to energy usages of individual appliances, thus greatly cutting down the cost i…
Addressing the Vulnerability of NMT in Input Perturbations
Weiwen Xu, Ai Ti Aw, Yang Ding +2
Neural Machine Translation (NMT) has achieved significant breakthrough in performance but is known to suffer vulnerability to input perturbations. As real input noise is difficult…