Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
Packet sampling techniques introduce measurement errors that should be carefully handled in order to correctly characterize the network behavior. In the literature several works h...
Code and design smells are recurring design problems in software systems that must be identified to avoid their possible negative consequences on development and maintenance. Conse...
: This paper presents a domain decomposition (DD) technique for efficient simulation of large-scale linear circuits such as power distribution networks. Simulation results show th...
Quming Zhou, Kai Sun, Kartik Mohanram, Danny C. So...