The fundamental statistical strategy of improving sampling efficiency through partitioning the population is applied to software testing. Usage models make it possible to apply th...
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
This paper addresses the problem of object tracking in image sequences. The approach taken is based upon adaptive statistical models. An object selected in a frame by a user is tr...
We propose several techniques for improving statistical machine translation between closely-related languages with scarce resources. We use character-level translation trained on ...
Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...