Stochastic simulations and other scientific applications that depend on random numbers are increasingly implemented in a parallelized manner in programmable logic. High-quality ps...
In this paper, we propose an unsupervised segmentation algorithm for extracting moving objects/regions from compressed video using Markov Random Field (MRF) classification. First,...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
Path-oriented Random Testing (PRT) aims at generating a uniformly spread out sequence of random test data that activate a single control flow path within an imperative program. T...
We present a method of chunking in Korean texts using conditional random fields (CRFs), a recently introduced probabilistic model for labeling and segmenting sequence of data. In a...