This paper presents a probabilistic algorithm for segmenting and recognizing text embedded in video sequences. The algorithm approximates the posterior distribution of segmentatio...
Recent advances in statistical machine translation have used approximate beam search for NP-complete inference within probabilistic translation models. We present an alternative ap...
Abhishek Arun, Barry Haddow, Philipp Koehn, Adam L...
Statistical static timing analysis (SSTA) has emerged as an essential tool for nanoscale designs. Monte Carlo methods are universally employed to validate the accuracy of the appr...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
—Continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles. By solving the manybody Schr¨odinge...
Kenneth Esler, Jeongnim Kim, David M. Ceperley, Lu...