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Equivalence Classes
"... Considerable efforts in recent years have been dedicated towards the specification of the conditions under which organisms learn to behave symbolically with two or more stimuli. Environmental stimuli are said to be “symbolic” for one another when they are shown to be equivalent; in other words, the ..."
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entered into an equivalence class (Sidman, 1994), and are thus symbolically related to one another. It is worth noting that symbolic behavior refers only to the bidirectional nature of human verbal behavior. Verballyable humans respond to one event in terms of the other: The Yors A. Garcia is a
Defining functions on equivalence classes
 ACM Transactions on Computational Logic
"... A quotient construction defines an abstract type from a concrete type, using an equivalence relation to identify elements of the concrete type that are to be regarded as indistinguishable. The elements of a quotient type are equivalence classes: sets of equivalent concrete values. Simple techniques ..."
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Cited by 12 (2 self)
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A quotient construction defines an abstract type from a concrete type, using an equivalence relation to identify elements of the concrete type that are to be regarded as indistinguishable. The elements of a quotient type are equivalence classes: sets of equivalent concrete values. Simple techniques
Equivalence Class Analysis Of Genetic Algorithms
 COMPLEX SYSTEMS
, 1991
"... The conventional understanding of genetic algorithms depends upon analysis by schemata and the notion of intrinsic parallelism. For this reason, only kary string representations have had any formal basis and nonstandard representations and operators have been regarded largely as heuristics, rather ..."
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Cited by 111 (9 self)
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, rather than principled algorithms. This paper extends the analysis to general representations through identification of schemata as equivalence classes induced by implicit equivalence relations over the space of chromosomes.
Learning Equivalence Classes Of Bayesian Network Structures
, 1996
"... Approaches to learning Bayesian networks from data typically combine a scoring metric with a heuristic search procedure. Given aBayesian network structure, many of the scoring metrics derived in the literature return a score for the entire equivalence class to which the structure belongs. When ..."
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Cited by 176 (1 self)
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Approaches to learning Bayesian networks from data typically combine a scoring metric with a heuristic search procedure. Given aBayesian network structure, many of the scoring metrics derived in the literature return a score for the entire equivalence class to which the structure belongs
Equivalence Class Subset Algorithm
"... Abstract—The equivalence class subset algorithm is a powerful tool for solving a wide variety of constraint satisfaction problems and is based on the use of a decision function which has a very high but not perfect accuracy. Perfect accuracy is not required in the decision function as even a subopti ..."
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Abstract—The equivalence class subset algorithm is a powerful tool for solving a wide variety of constraint satisfaction problems and is based on the use of a decision function which has a very high but not perfect accuracy. Perfect accuracy is not required in the decision function as even a
EQUIVALENCE CLASSES OF IDEALS IN THE
"... Abstract. An equivalence relation is defined and studied on the set of Bstable ideals in the nilradical of the Lie algebra of a Borel subgroup B. Techniques are developed to compute the equivalence relation and these are carried out in the exceptional groups. There is a natural partial order on equ ..."
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on equivalence classes coming from inclusion of one ideal in another. A main theorem is that this partial order is a refinement of the closure ordering on nilpotent orbits. Let G be a connected simple algebraic group over C and B a Borel subgroup of G. Let g be the Lie algebra of G and b the Lie algebra of B
A characterization of Markov equivalence classes for acyclic digraphs
, 1995
"... Undirected graphs and acyclic digraphs (ADGs), as well as their mutual extension to chain graphs, are widely used to describe dependencies among variables in multivariate distributions. In particular, the likelihood functions of ADG models admit convenient recursive factorizations that often allow e ..."
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Cited by 120 (7 self)
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of all ADGs with a given set of vertices is naturally partitioned into Markovequivalence classes, each class being associated with a unique statistical model. Statistical procedures, such as model selection or model averaging, that fail to take into account these equivalence classes, may incur
Equivalence Class Universal Cycles for Permutations
 Discrete Math
, 1997
"... Introduction In this note we describe a representation of permuations of an nelement set that can be viewed as equivalence classes of permuations of length n on n + 1 symbols. An equivalence class universal cycle is a string x 1 x 2 ; : : : ; x n! such that among the n! length n substrings x i x i ..."
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Introduction In this note we describe a representation of permuations of an nelement set that can be viewed as equivalence classes of permuations of length n on n + 1 symbols. An equivalence class universal cycle is a string x 1 x 2 ; : : : ; x n! such that among the n! length n substrings x i x
Nodal Stimulus Equivalence Classes
"... The term stimulus equivalence (SE) refers to the emergence of new, untaught relations between a set of stimuli derived from a minimal number of trained relations that have previously been established between them. Relations are trained between pairs of stimuli, and all the pairs within a given set ..."
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The term stimulus equivalence (SE) refers to the emergence of new, untaught relations between a set of stimuli derived from a minimal number of trained relations that have previously been established between them. Relations are trained between pairs of stimuli, and all the pairs within a given set
ON AN EQUIVALENT CLASS OF NORMS FOR BMO
, 1987
"... The BMO norm of / is equivalent to sup (f\f(y)u(x,t)\"Pt(xy)dy \, where Pt is the Poisson kernel. In this note, we show that Pt can be replaced by a nonnegative radial function h, which is positive in a neighbourhood of 0, with J h(x) dx = 1 and J r™ " 1 (Inr) p h(r) dr < oo, where h ..."
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The BMO norm of / is equivalent to sup (f\f(y)u(x,t)\"Pt(xy)dy \, where Pt is the Poisson kernel. In this note, we show that Pt can be replaced by a nonnegative radial function h, which is positive in a neighbourhood of 0, with J h(x) dx = 1 and J r™ " 1 (Inr) p h(r) dr < oo, where h
Results 1  10
of
11,902