In this paper, we introduce two new formulations for multi-class multi-kernel relevance vector machines (mRVMs) that explicitly lead to sparse solutions, both in samples and in nu...
Theodoros Damoulas, Yiming Ying, Mark A. Girolami,...
We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset. While there are asymptotically correct...
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
We present a correlated bigram LSA approach for unsupervised LM adaptation for automatic speech recognition. The model is trained using efficient variational EM and smoothed using...