We describe an algorithm for converting a characteristic set of a prime differential ideal from one ranking into another. This algorithm was implemented in many different language...
Robotic sensor networks are more powerful than sensor networks because the sensors can be moved by the robots to adjust their sensing coverage. In robotic sensor networks, an impor...
Let g be an element of prime order p in an abelian group and let Zp. We show that if g, g , and gd are given for a positive divisor d of p - 1, the secret key can be computed de...
An original algorithm is presented that generates both restricted integer compositions and restricted integer partitions that can be constrained simultaneously by a) upper and low...
Logic-based probabilistic models (LBPMs) enable us to handle problems with uncertainty succinctly thanks to the expressive power of logic. However, most of LBPMs have restrictions...
For a given target node T and a given depth k 1, we propose an algorithm for discovering a local causal network around the target T to depth k. In our algorithm, we find parents,...
It is probably fair to say that exact inference in graphical models is considered a solved problem, at least regarding its computational complexity: it is exponential in the treew...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
We explore automated discovery of topicallycoherent segments in speech or text sequences. We give two new discriminative topic segmentation algorithms which employ a new measure o...
Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...