We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
In this paper, we investigate the use of the coupled hidden Markov models (CHMM) for the task of audio-visual text dependent speaker identification. Our system determines the iden...
Tieyan Fu, Xiao Xing Liu, Lu Hong Liang, Xiaobo Pi...
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...
In Proc. of IEEE Conf. on CVPR'03, Madison, Wisconsin, 2003 We propose a generative model approach to contour tracking against non-stationary clutter and to coping with occlu...