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The paper presents and evaluates the power of a new scheme that generates search heuristics mechanically for problems expressed using a set of functions or relations over a finite set of variables. The heuristics are extracted from a parameterized approximation scheme called Mini-Bucket elimination that allows controlled trade-off between computation and(More)
The paper evaluates empirically the suit-ability of Stochastic Local Search algorithms (SLS) for nding most probable explanations in Bayesian networks. SLS algorithms (e.g., GSAT, WSAT [16]) have recently proven to be highly eective in solving complex constraint-satisfaction and sat-isability problems which cannot be solved by traditional search s c hemes.(More)
Many receptor mutants were generated and several NH2-terminally modified galanin analogs synthesized to define the regions of hGalR1 involved in galanin binding. Ligand binding properties and functionality of mutant receptors were evaluated. The His264Ala and Phe282Ala receptor mutants, although deficient in binding in the concentration range of galanin(More)
The chimeric peptide M35 [galanin(1-13)-bradykinin(2-9) amide] is a high-affinity galanin receptor ligand acting as a galanin receptor antagonist in the rat spinal cord, rat hippocampus and isolated mouse pancreatic islets. We have radiolabelled M35 and performed equilibrium binding studies with [125I]M35 on the rat pancreatic beta-cell line Rin m 5F,(More)
This paper evaluates the power of a new scheme that generates search heuristics mechanically. This approach w as presented and evaluated rst in the context of optimization in belief networks. In this paper we extend this work to Max-CSP. The approach i n volves extracting heuristics from a parameterized approximation scheme called Mini-Bucket elimination(More)
Computing lower bounds to the best-cost extension of a tu-ple is an ubiquous task in constraint optimization. A particular case of special interest is the computation of lower bounds to all singleton tu-ples, since it permits domain pruning in Branch and Bound algorithms. In this paper we introduce MCTE(z), a general algorithm which allows the computation(More)
It has been shown that hill-climbing constraint satisfaction methods like min-conflicts [Minton et a/., 1990] and GSAT [Selman et a/., 1992] can outperform complete systematic search methods like backtracking and backjumping on many large classes of problems. In this paper we investigate how preprocessing improves GSAT. In particular, we will focus on the(More)
The paper investigates parameterized approximate message-passing schemes that are based on bounded inference and are inspired by Pearl's belief propagation algorithm (BP). We start with the bounded inference mini-clustering algorithm and then move to the iterative scheme called Iterative Join-Graph Propagation (IJGP), that combines both iteration and(More)
We propose a propositional language for temporal reasoning that is computationally effective yet expressive enough to describe information about fluents, events and temporal constraints. Although the complete inference algorithm is exponential, we characterize a tractable core with limited expressibility and inferential power. Our results render a variety(More)
This paper describes our entry for the MAP/MPE track of the PASCAL 2011 Probabilistic Inference Challenge, which placed first in all three time limit categories , 20 seconds, 20 minutes, and 1 hour. Our baseline is a branch-and-bound algorithm that explores the AND/OR context-minimal search graph of a graphical model guided by a mini-bucket heuristic.(More)