— Language and image understanding are two major goals of artificial intelligence which can both be conceptually formulated in terms of parsing the input signal into a hierarchi...
Long Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan...
We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...
In this paper we propose a cascaded hierarchical framework for object detection and tracking. We claim that, by integrating both detection and tracking into a unified framework, t...
Specification and verification of real-time systems are important research topics which have practical implications. In this work, we present a self-contained toolkit to analyze r...
This paper describes a novel method for explaining Bayesian network (BN) inference when the network is modeling a population of conditionally independent agents, each of which is m...