This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
A regression model in the tensorPCA subspace is proposed in this paper for face super-resolution reconstruction. An approximate conditional probability model is used for the tenso...
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
A fusion scheme of phone duration models (PDMs) is presented in this work. Specifically, a support vector regression (SVR)-fusion model is fed with the predictions of a group of i...