Multi-language evaluation of exact solvers in graphical model discrete optimization
By representing the constraints and objective function in factorized form, graphical models
can concisely define various NP-hard optimization problems. They are therefore extensively …
can concisely define various NP-hard optimization problems. They are therefore extensively …
[HTML][HTML] Computational protein design as an optimization problem
Proteins are chains of simple molecules called amino acids. The three-dimensional shape of
a protein and its amino acid composition define its biological function. Over millions of years …
a protein and its amino acid composition define its biological function. Over millions of years …
Variable neighborhood search for graphical model energy minimization
Graphical models factorize a global probability distribution/energy function as the
product/sum of local functions. A major inference task, known as MAP in Markov Random …
product/sum of local functions. A major inference task, known as MAP in Markov Random …
Virtual pairwise consistency in cost function networks
In constraint satisfaction, pairwise consistency (PWC) is a well-known local consistency
improving generalized arc consistency in theory but not often in practice. A popular …
improving generalized arc consistency in theory but not often in practice. A popular …
MAP Inference Via -Sphere Linear Program Reformulation
Maximum a posteriori (MAP) inference is an important task for graphical models. Due to
complex dependencies among variables in realistic models, finding an exact solution for …
complex dependencies among variables in realistic models, finding an exact solution for …
Anytime anyspace AND/OR search for bounding the partition function
Bounding the partition function is a key inference task in many graphical models. In this
paper, we develop an anytime anyspace search algorithm taking advantage of AND/OR tree …
paper, we develop an anytime anyspace search algorithm taking advantage of AND/OR tree …
[PDF][PDF] Recursive Best-First AND/OR Search for Optimization in Graphical Models.
The paper presents and evaluates the power of limited memory best-first search over
AND/OR spaces for optimization tasks in graphical models. We propose Recursive Best-First …
AND/OR spaces for optimization tasks in graphical models. We propose Recursive Best-First …
Exact and approximate inference in graphical models: variable elimination and beyond
Probabilistic graphical models offer a powerful framework to account for the dependence
structure between variables, which is represented as a graph. However, the dependence …
structure between variables, which is represented as a graph. However, the dependence …
Computational protein design using AND/OR branch-and-bound search
The computation of the global minimum energy conformation (GMEC) is an important and
challenging topic in structure-based computational protein design. In this article, we propose …
challenging topic in structure-based computational protein design. In this article, we propose …
Exact or approximate inference in graphical models: why the choice is dictated by the treewidth, and how variable elimination can be exploited
Probabilistic graphical models offer a powerful framework to account for the dependence
structure between variables, which is represented as a graph. However, the dependence …
structure between variables, which is represented as a graph. However, the dependence …