We describe two market-inspired approaches to propositional satisfiability. Whereas a previous market-inspired approach exhibited extremely slow performance, we find that variatio...
William E. Walsh, Makoto Yokoo, Katsutoshi Hirayam...
Recently, there have been several advances in the machine learning and pattern recognition communities for developing manifold learning algorithms to construct nonlinear low-dimen...
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian m...
In previous work on "transformed mixtures of Gaussians" and "transformed hidden Markov models", we showed how the EM algorithm in a discrete latent variable mo...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the "aboutness" of a corpus of scientific and technical publications by ...