FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2741070676> ?p ?o ?g. }

• W2741070676 abstract "The task of finding the most probable explanation (or MAP) in a graphical model comes up in a wide range of applications including image understanding [9], error correcting codes [2] and protein folding [11]. For an arbitrary graph, this problem is known to be NP hard [8] and various approximation algorithms have been proposed (see. e.g [5] for a recent review). Linear Programming (LP) Relaxations are a standard method for approximating combinatorial optimization problems in computer science [1]. They have been used for approximating the MAP problem in a general graphical model by Santos [7]. More recently LP relaxations have been used for error-correcting codes [2], and for protein folding [4]. LP relaxations have an advantage over other approximate inference schemes in that they come with an optimality guarantee when the solution to the linear program is integer, then the LP solution is guaranteed to give the global optimum of the posterior probability. The research described here grew out of our experience in using LP relaxations for problems in computer vision, computational biology and statistical physics. In all these fields, the number of variables in a realistic problem may be on the order of 10 or more. We found that using standard, off-the-shelf LP solvers these problems cannot be solved using standard desktop hardware. A second problem, is that even when we worked on toy problems in which the number of variables was much smaller, we found that a large fraction of the variables in the LP solution were non-integer. This means that the guarantee of optimality is lost, and in practice thresholding the fractional LP solutions gave poor results. The fact that general purpose LP solvers are not suitable for these problems is not that surprising. The linear programs that arise out of LP relaxations for graphical models have a common structure and are a small subset of all possible linear programs. The challenge is to find a LP solver that (1) takes advantage of this special structure and (2) can be used to solve a hierarchy of tighter relaxations in case the standard LP relaxation fails. In this paper, we show that generalized belief propagation with a convex free energy provides such a solver. We show that tree reweighted BP suggested by Wainwright and colleagues [10] is a special case of GBP with a convex free energy but there are many convex free energies that cannot be represented as a tree reweighted free energy. This result has theoretical implications since it shows that the property of solving the LP is distinct from the property of providing a rigorous bound 1E-mail: yweiss@cs.huji.ac.il" @default.
• W2741070676 created "2017-08-08" @default.
• W2741070676 creator A5022114369 @default.
• W2741070676 creator A5079364492 @default.
• W2741070676 creator A5088725286 @default.
• W2741070676 date "2005-01-01" @default.
• W2741070676 modified "2023-09-27" @default.
• W2741070676 title "Linear Programming and Belief Propagation with Convex Free Energies Applications in Computer Vision and Computational Biology" @default.
• W2741070676 cites W1546981760 @default.
• W2741070676 cites W1762430620 @default.
• W2741070676 cites W2100034662 @default.
• W2741070676 cites W2101712920 @default.
• W2741070676 cites W2118696796 @default.
• W2741070676 cites W2130178369 @default.
• W2741070676 cites W2132860887 @default.
• W2741070676 cites W2150734839 @default.
• W2741070676 cites W2169282664 @default.
• W2741070676 cites W2169415915 @default.
• W2741070676 hasPublicationYear "2005" @default.
• W2741070676 type Work @default.
• W2741070676 sameAs 2741070676 @default.
• W2741070676 citedByCount "0" @default.
• W2741070676 crossrefType "journal-article" @default.
• W2741070676 hasAuthorship W2741070676A5022114369 @default.
• W2741070676 hasAuthorship W2741070676A5079364492 @default.
• W2741070676 hasAuthorship W2741070676A5088725286 @default.
• W2741070676 hasConcept C105795698 @default.
• W2741070676 hasConcept C11413529 @default.
• W2741070676 hasConcept C126255220 @default.
• W2741070676 hasConcept C134261354 @default.
• W2741070676 hasConcept C152948882 @default.
• W2741070676 hasConcept C154945302 @default.
• W2741070676 hasConcept C159985019 @default.
• W2741070676 hasConcept C192562407 @default.
• W2741070676 hasConcept C199360897 @default.
• W2741070676 hasConcept C204323151 @default.
• W2741070676 hasConcept C2776214188 @default.
• W2741070676 hasConcept C33923547 @default.
• W2741070676 hasConcept C41008148 @default.
• W2741070676 hasConcept C41045048 @default.
• W2741070676 hasConcept C56086750 @default.
• W2741070676 hasConcept C57273362 @default.
• W2741070676 hasConcept C80444323 @default.
• W2741070676 hasConcept C97137487 @default.
• W2741070676 hasConceptScore W2741070676C105795698 @default.
• W2741070676 hasConceptScore W2741070676C11413529 @default.
• W2741070676 hasConceptScore W2741070676C126255220 @default.
• W2741070676 hasConceptScore W2741070676C134261354 @default.
• W2741070676 hasConceptScore W2741070676C152948882 @default.
• W2741070676 hasConceptScore W2741070676C154945302 @default.
• W2741070676 hasConceptScore W2741070676C159985019 @default.
• W2741070676 hasConceptScore W2741070676C192562407 @default.
• W2741070676 hasConceptScore W2741070676C199360897 @default.
• W2741070676 hasConceptScore W2741070676C204323151 @default.
• W2741070676 hasConceptScore W2741070676C2776214188 @default.
• W2741070676 hasConceptScore W2741070676C33923547 @default.
• W2741070676 hasConceptScore W2741070676C41008148 @default.
• W2741070676 hasConceptScore W2741070676C41045048 @default.
• W2741070676 hasConceptScore W2741070676C56086750 @default.
• W2741070676 hasConceptScore W2741070676C57273362 @default.
• W2741070676 hasConceptScore W2741070676C80444323 @default.
• W2741070676 hasConceptScore W2741070676C97137487 @default.
• W2741070676 hasLocation W27410706761 @default.
• W2741070676 hasOpenAccess W2741070676 @default.
• W2741070676 hasPrimaryLocation W27410706761 @default.
• W2741070676 hasRelatedWork W1626012029 @default.
• W2741070676 hasRelatedWork W2008854809 @default.
• W2741070676 hasRelatedWork W2088248957 @default.
• W2741070676 hasRelatedWork W2115058129 @default.
• W2741070676 hasRelatedWork W2146883452 @default.
• W2741070676 hasRelatedWork W2290515589 @default.
• W2741070676 hasRelatedWork W2299801417 @default.
• W2741070676 hasRelatedWork W2588151466 @default.
• W2741070676 hasRelatedWork W2609365846 @default.
• W2741070676 hasRelatedWork W2778898806 @default.
• W2741070676 hasRelatedWork W2903344726 @default.
• W2741070676 hasRelatedWork W2909461591 @default.
• W2741070676 hasRelatedWork W3002597283 @default.
• W2741070676 hasRelatedWork W3033234379 @default.
• W2741070676 hasRelatedWork W3104221628 @default.
• W2741070676 hasRelatedWork W3204618682 @default.
• W2741070676 hasRelatedWork W633277346 @default.
• W2741070676 hasRelatedWork W2468862862 @default.
• W2741070676 hasRelatedWork W2592224851 @default.
• W2741070676 hasRelatedWork W3140817845 @default.
• W2741070676 isParatext "false" @default.
• W2741070676 isRetracted "false" @default.
• W2741070676 magId "2741070676" @default.
• W2741070676 workType "article" @default.