We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Multibiometric systems fuse information from different sources to compensate for the limitations in performance of individual matchers. We propose a framework for optimal combinati...
Karthik Nandakumar, Yi Chen, Sarat C. Dass, Anil K...
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
We describe CoSP, a general framework for conducting computational soundness proofs of symbolic models and for embedding these proofs into formal calculi. CoSP considers arbitrary...
With the recent availability of commercial light field cameras, we can foresee a future in which light field signals will be as common place as images. Hence, there is an immine...