Results 1  10
of
346,342
Machine Translation as Tree Labeling
"... We present the main ideas behind a new syntaxbased machine translation system, based on reducing the machine translation task to a treelabeling task. This tree labeling is further reduced to a sequence of decisions (of four varieties), which can be discriminatively trained. The optimal tree labeli ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
labeling (i.e. translation) is then found through a simple depthfirst branchandbound search. An early system founded on these ideas has been shown to be competitive with Pharaoh when both are trained on a small subsection of the Europarl corpus. 1
DepthFirst MiniBucket Elimination
"... Abstract. Many important combinatorial optimization problems can be expressed as constraint satisfaction problems with soft constraints. When problems are too difficult to be solved exactly, approximation methods become the best option. Minibucket elimination (MBE) is a well known approximation met ..."
Abstract
 Add to MetaCart
Abstract. Many important combinatorial optimization problems can be expressed as constraint satisfaction problems with soft constraints. When problems are too difficult to be solved exactly, approximation methods become the best option. Minibucket elimination (MBE) is a well known approximation method for combinatorial optimization problems. It has a control parameter z that allow us to trade time and space for accuracy. In practice it is the space and not the time that limits the execution with high values of z. In this paper we introduce a set of improvements on the way MBE handles memory. The resulting algorithm dfMBE may be orders of magnitude more efficient. As a consequence, higher values of z can be used which, in turn, yields significantly better bounds. We demonstrate our approach in scheduling, probabilistic reasoning and resource allocation problems. 1 Introduction Constraint satisfaction problems (CSPs) involve the assignment of a set of variables subject to a set of constraints. The addition of soft constraints [1] extend the CSP framework to optimization tasks (we will assume optimization as minimization). Many problems in a variety of domains such as probabilistic reasoning [2], bioinformatics [3], scheduling [4], etc, can be naturally expressed as soft CSPs.In recent years a big effort has been made in the development of algorithms to solve this type of problems. In some cases, specialized algorithms can be designedto solve more efficiently particular problems. Nevertheless in this paper we will focus on general techniques.
Parallel algorithms for depthfirst search
, 1991
"... Parallel Algorithms for DepthFirst Search In this paper we examine parallel algorithms for performing a depthfirst search (DFS) of a directed or undirected graph in sublinear time. this subject is interesting in part because DFS seemed at first to be an inherently sequential process, and for a lo ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
Parallel Algorithms for DepthFirst Search In this paper we examine parallel algorithms for performing a depthfirst search (DFS) of a directed or undirected graph in sublinear time. this subject is interesting in part because DFS seemed at first to be an inherently sequential process, and for a
BestFirst and DepthFirst Minimax Search in Practice
"... Most practitioners use a variant of the AlphaBeta algorithm, a simple depthfirst procedure, for searching minimax trees. SSS*, with its bestfirst search strategy, reportedly offers the potential for more efficient search. However, the complex formulation of the algorithm and its alleged excessive ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
Most practitioners use a variant of the AlphaBeta algorithm, a simple depthfirst procedure, for searching minimax trees. SSS*, with its bestfirst search strategy, reportedly offers the potential for more efficient search. However, the complex formulation of the algorithm and its alleged
Make  a program for maintaining computer programs
, 1979
"... In a programming project, it is easy to lose track of which files need to be reprocessed or recompiled after a change is made in some part of the source. Make provides a simple mechanism for maintaining uptodate versions of programs that result from many operations on a number of files. It is poss ..."
Abstract

Cited by 352 (0 self)
 Add to MetaCart
the graph of dependencies; Make does a depthfirst search of this graph to determine what work is really necessary. Make also provides a simple macro substitution facility and the ability to encapsulate commands in a single file for convenient administration.
Depthfirst search solves Peg Solitaire
, 1998
"... We invite the reader to test his skillness in previewing the behaviour of a simple, depthfirst search algorithm that solves (or tries to solve) the Pegsolitaire game; the test is based on a few questions about the search tree involving aspects such as the number of nodes explored by the algorithm, ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
Introduction The efficiency of depthfirst search algorithms and the use of heuristics to speed up the search have always been an important practical issue in Artificial Intelligence. This paper concerns the use of a simple depthfirst algorithm for the old game of Peg Solitaire and some of its variants
Scalability of Massively Parallel DepthFirst Search
 In DIMACS Workshop
, 1994
"... .We analyze and compare the scalabilityoftwo generic schemes for heuristic depth#rst search on highly parallel MIMD systems. The #rst one employs a task attraction mechanism where the work packets are generated on demand by splitting the donor's stack. Analytical and empirical analyses sho ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
.We analyze and compare the scalabilityoftwo generic schemes for heuristic depth#rst search on highly parallel MIMD systems. The #rst one employs a task attraction mechanism where the work packets are generated on demand by splitting the donor's stack. Analytical and empirical analyses
A depthfirst approach to targetvalue search
"... In this paper, we consider how to improve the scalability and efficiency of targetvalue path search on directed acyclic graphs. To this end, we introduce a depthfirst heuristic search algorithm and a dynamicprogramming method to compute the heuristic’s pattern database in linear (in the number of ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
In this paper, we consider how to improve the scalability and efficiency of targetvalue path search on directed acyclic graphs. To this end, we introduce a depthfirst heuristic search algorithm and a dynamicprogramming method to compute the heuristic’s pattern database in linear (in the number
An Extended Depthfirst Search –How to Decrease Backtracking –
"... In usual algorithms based on the depthfirst search, there is no problem about this method. The number of steps for this search is $\ominus(V+E) $. So most people have paid no attention to this method. However, there are some areas, say distributed algorithms, in which one step costs much time. In p ..."
Abstract
 Add to MetaCart
In usual algorithms based on the depthfirst search, there is no problem about this method. The number of steps for this search is $\ominus(V+E) $. So most people have paid no attention to this method. However, there are some areas, say distributed algorithms, in which one step costs much time
DepthFirst Search and Strong Connectivity in Coq
"... Using Coq, we mechanize Wegener’s proof of Kosaraju’s lineartime algorithm for computing the strongly connected components of a directed graph. Furthermore, also in Coq, we define an executable and terminating depthfirst search algorithm. 1. ..."
Abstract
 Add to MetaCart
Using Coq, we mechanize Wegener’s proof of Kosaraju’s lineartime algorithm for computing the strongly connected components of a directed graph. Furthermore, also in Coq, we define an executable and terminating depthfirst search algorithm. 1.
Results 1  10
of
346,342