Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
We propose a new approach for the restoration of polarimetric Stokes images, capable of simultaneously segmenting and restoring the images. In order to easily handle the admissibi...
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...