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Minimal Ordering Constraints for some Families of Variable Symmetries
"... Existing methods of breaking all variable symmetries in a constraint satisfaction problem over n variables, by adding lexicographic ordering constraints, can require n! new constraints. This adds an unacceptable overhead to the solving process. In certain cases, for example when the variables are co ..."
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Existing methods of breaking all variable symmetries in a constraint satisfaction problem over n variables, by adding lexicographic ordering constraints, can require n! new constraints. This adds an unacceptable overhead to the solving process. In certain cases, for example when the variables
Minimal Ordering Constraints for some Families of Variable Symmetries
"... Abstract. Variable symmetries in a constraint satisfaction problem can be broken by adding lexicographic ordering constraints. Existing general methods of generating such sets of ordering constraints can require a huge number of constraints. This adds an unacceptable overhead to the solving process. ..."
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. Methods exist by which this large set of ordering constraints can be reduced to a much smaller set automatically, but their application is also prohibitively costly. In contrast, this paper takes a bottomup approach. It examines some commonlyoccurring families of groups and derives a minimal set
Rule 1,2Minimal Ordering Constraints for some Families of Variable Symmetries
"... Abstract. General methods of breaking all variable symmetries by adding lexicographic ordering constraints can require a huge number of constraints. This adds an unacceptable overhead to the solving process. In certain cases, this set can be reduced dramatically. For example, Puget has shown that wh ..."
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that when n symmetric variables are constrained to take distinct values, a set of nā1 binary ordering constraints is sufficent to break all the variable symmetry. This paper studies some commonlyoccuring families of groups and shows how the set of ordering constraints can be reduced in each case. 1
Homological Algebra of Mirror Symmetry
 in Proceedings of the International Congress of Mathematicians
, 1994
"... Mirror Symmetry was discovered several years ago in string theory as a duality between families of 3dimensional CalabiYau manifolds (more precisely, complex algebraic manifolds possessing holomorphic volume elements without zeroes). The name comes from the symmetry among Hodge numbers. For dual Ca ..."
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Cited by 529 (3 self)
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Mirror Symmetry was discovered several years ago in string theory as a duality between families of 3dimensional CalabiYau manifolds (more precisely, complex algebraic manifolds possessing holomorphic volume elements without zeroes). The name comes from the symmetry among Hodge numbers. For dual
Constraint Networks
, 1992
"... Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint expression ..."
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Cited by 1149 (43 self)
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Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint
An introduction to variable and feature selection
 Journal of Machine Learning Research
, 2003
"... Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. ..."
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Cited by 1283 (16 self)
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Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available.
Concurrent Constraint Programming
, 1993
"... This paper presents a new and very rich class of (concurrent) programming languages, based on the notion of comput.ing with parhal information, and the concommitant notions of consistency and entailment. ā In this framework, computation emerges from the interaction of concurrently executing agent ..."
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Cited by 502 (16 self)
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agents that communicate by placing, checking and instantiating constraints on shared variables. Such a view of computation is interesting in the context of programming languages because of the ability to represent and manipulate partial information about the domain of discourse, in the con
The Semantics Of Constraint Logic Programs
 JOURNAL OF LOGIC PROGRAMMING
, 1996
"... This paper presents for the first time the semantic foundations of CLP in a selfcontained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new and comp ..."
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Cited by 872 (14 self)
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and complete proofs for the main lemmas. Importantly, we clarify which theorems depend on conditions such as solution compactness, satisfaction completeness and independence of constraints. Second, we generalize the original results to allow for incompleteness of the constraint solver. This is important
Constraint Logic Programming: A Survey
"... Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve in differe ..."
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Cited by 864 (25 self)
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Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve
Large margin methods for structured and interdependent output variables
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
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Cited by 612 (12 self)
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the complementary issue of designing classification algorithms that can deal with more complex outputs, such as trees, sequences, or sets. More generally, we consider problems involving multiple dependent output variables, structured output spaces, and classification problems with class attributes. In order
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