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Approximate Inference Using Planar Graph Decomposition

Approximate Inference Using Planar Graph Decomposition

Approximate Inference Using Planar Graph Decomposition. Amir Globerson and Tommi Jaakkola In Advances in Neural Information Processing Systems 19 , 2006 . Presented by Jonathan Huang at SELECT Lab, 12/12/06. The Ising Model. Let G=(V,E) be a graph

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582 views • 38 slides
1. Extraction Operators

1. Extraction Operators

1. Extraction Operators. Projection Selection Unorder Join Cartesian Product Union Difference Intersection. set-like operators (commutativity). Projection ?[ type, name ]( e: expression )

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201 views • 14 slides
1. Extraction Operators

1. Extraction Operators

1. Extraction Operators. Projection Selection Unorder Join Cartesian Product Union Difference Intersection. set-like operators (commutativity). Projection ?[ type, name ]( e: expression )

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147 views • 14 slides
Function Transformations

Function Transformations

Function Transformations. Notes from Adv Algebra Week of Sept 24, 2012. Transformation(s). This means the graphed line can move on the graph. The vertex can move up or down or left or right. The original (or parent function ) vertex was at 0,0 (the blue dot).

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243 views • 12 slides
Tree Decompositions and Fixed Parameter Tractability of k -Path

Tree Decompositions and Fixed Parameter Tractability of k -Path

Tree Decompositions and Fixed Parameter Tractability of k -Path. Tree Decomposition. Every edge is in a red ellipse (the bags). The bags are connected in a tree . The bags an original vertex is part of are connected . Example : Independent Set. The root. The k-Path Problem.

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233 views • 11 slides

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