Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
We describe a class of translation model in which a set of input variants encoded as a context-free forest is translated using a finitestate translation model. The forest structur...
This paper proposes an original inhomogeneous restoration (deconvolution) model under the Bayesian framework. In this model, regularization is achieved, during the iterative resto...
After the emergence of numerous Internet streaming applications, rate-distortion (R-D) modeling of scalable video encoders has become an important issue. In this paper, we examine...
We propose a binary Markov Random Field (MRF) model
that assigns high probability to regions in the image domain
consisting of an unknown number of circles of a given radius.
We...