This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
The notion of local features in space-time has recently been proposed to capture and describe local events in video. When computing space-time descriptors, however, the result may...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In this paper, we propose a novel appearance-based representation, called Structured Ordinal Feature (SOF). SOF is a binary string encoded by combining eight ordinal blocks in a ci...
ShengCai Liao, Zhen Lei, Stan Z. Li, Xiaotong Yuan...
The collection of behavior protocols is a common practice in human factors research, but the analysis of these large data sets has always been a tedious and time-consuming process....
Walter C. Mankowski, Peter Bogunovich, Ali Shokouf...