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We introduce the Spherical Admixture Model (SAM), a Bayesian topic model for arbitrary 2 normalized data. SAM maintains the same hierarchical structure as Latent Dirichlet Allocation (LDA), but models documents as points on a high-dimensional spherical manifold, allowing a natural likelihood parameterization in terms of cosine distance. Furthermore, SAM can… (More)

Different solvers for computationally difficult problems such as satisfiability (SAT) perform best on different instances. Algorithm portfolios exploit this phenomenon by predicting solvers' performance on specific problem instances, then shifting computational resources to the solvers that appear best suited. This paper develops a new approach to the… (More)

- Bryan Silverthorn, Risto Miikkulainen, Martin Gebser, Benjamin Kaufmann, Torsten Schaub, Daniel Le Berre +2 others
- 2010

In Brief Algorithm portfolio methods (Huberman, Lukose, and Hogg 1997) use information about solvers and problem instances to allocate computational resources among multiple solvers, attempting to maximize the time spent on those well suited to each instance. Portfolio methods such as SATzilla (Xu et al. 2008) have proved increasingly effective in… (More)

Answer set programming (ASP) is a declarative programming formalism that allows a practitioner to specify a problem without describing an algorithm for solving it. In ASP, the tools for processing problem specifications are called answer set solvers. Because specified problems are often NP complete, these systems often require significant computational… (More)

The borg solver is an algorithm portfolio (Huberman, Lukose, and Hogg 1997). It uses empirical information about solvers and problem instances to allocate computational resources among multiple subsolvers, attempting to maximize the time spent on those well suited to each instance. Portfolio methods such as SATzilla (Xu et al. 2008) have proved increasingly… (More)

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