We consider an information-theoretic objective function for statistical modeling of time series that embodies a parametrized trade-off between the predictive power of a model and...
Susanne Still, James P. Crutchfield, Christopher J...
We propose a propositional language for temporal reasoning that is computationally effective yet expressive enough to describe information about fluents, events and temporal const...
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...
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 ...
With the invention of microarray technology, researchers are able to measure the expression levels of ten thousands of genes in parallel at various time points of a biological proc...
Christian Spieth, Felix Streichert, Nora Speer, An...