We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
—Due to the dynamic nature of grid environments, schedule algorithms always need assistance of a long-time-ahead load prediction to make decisions on how to use grid resources ef...
Probabilistic language models are critical to applications in natural language processing that include speech recognition, optical character recognition, and interfaces for text e...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
This paper presents a method to characterize Nyquist rate A/D converters based on the use of a first order statistical behavioral model. The proposed model is derived from a very...