We present a neural network method for inducing representations of parse histories and using these history representations to estimate the probabilities needed by a statistical le...
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...
Integrating Parts of Speech (POS) information to Machine Translation (MT) model usually amounts to significant changes in the MT decoder. We present a method to rapidly integrate...
We consider the problem of estimating the feedback coefficients of a linear feedback shift register (LFSR) based on noisy observations. In the current approach, the coefficients a...
Classifier calibration is the process of converting classifier scores into reliable probability estimates. Recently, a calibration technique based on isotonic regression has gain...