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210
Deterministic Nonmonotone Strategies for Effective Training of Multilayer Perceptrons
"... In this paper, we present deterministic nonmonotone learning strategies for multilayer perceptrons (MLPs), i.e., deterministic training algorithms in which error function values are allowed to increase at some epochs. To this end, we argue that the current error function value must satisfy a nonmono ..."
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Cited by 6 (4 self)
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In this paper, we present deterministic nonmonotone learning strategies for multilayer perceptrons (MLPs), i.e., deterministic training algorithms in which error function values are allowed to increase at some epochs. To this end, we argue that the current error function value must satisfy a
Nonmonotone Strategy for Minimization of Quadratics With Simple Constraints
, 1999
"... An algorithm for quadratic minimization with simple bounds is introduced, combining, as many wellknown methods do, active set strategies and projection steps. The novelty is that here the criterion for acceptance of a projected trial point is weaker than the usual ones, which are based on monotone ..."
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Cited by 7 (5 self)
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An algorithm for quadratic minimization with simple bounds is introduced, combining, as many wellknown methods do, active set strategies and projection steps. The novelty is that here the criterion for acceptance of a projected trial point is weaker than the usual ones, which are based on monotone
Using Maimonides’ Rule to Estimate the Effect of Class Size on Scholastic Achievement
 QUARTERLY JOURNAL OF ECONOMICS
, 1999
"... The twelfth century rabbinic scholar Maimonides proposed a maximum class size of 40. This same maximum induces a nonlinear and nonmonotonic relationship between grade enrollment and class size in Israeli public schools today. Maimonides’ rule of 40 is used here to construct instrumental variables e ..."
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Cited by 582 (40 self)
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The twelfth century rabbinic scholar Maimonides proposed a maximum class size of 40. This same maximum induces a nonlinear and nonmonotonic relationship between grade enrollment and class size in Israeli public schools today. Maimonides’ rule of 40 is used here to construct instrumental variables
Solving Nonlinear Systems Of Equations By Means Of QuasiNewton Methods With A Nonmonotone Strategy
, 1997
"... A nonmonotone strategy for solving nonlinear systems of equations is introduced. The idea consists of combining efficient local methods with an algorithm that reduces monotonically the squared norm of the system in a proper way. The local methods used are Newton's method and two quasiNewton alg ..."
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Cited by 13 (3 self)
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A nonmonotone strategy for solving nonlinear systems of equations is introduced. The idea consists of combining efficient local methods with an algorithm that reduces monotonically the squared norm of the system in a proper way. The local methods used are Newton's method and two quasi
Nonmonotone spectral projected gradient methods on convex sets
 SIAM Journal on Optimization
, 2000
"... Abstract. Nonmonotone projected gradient techniques are considered for the minimization of differentiable functions on closed convex sets. The classical projected gradient schemes are extended to include a nonmonotone steplength strategy that is based on the Grippo–Lampariello–Lucidi nonmonotone lin ..."
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Cited by 215 (28 self)
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Abstract. Nonmonotone projected gradient techniques are considered for the minimization of differentiable functions on closed convex sets. The classical projected gradient schemes are extended to include a nonmonotone steplength strategy that is based on the Grippo–Lampariello–Lucidi nonmonotone
A Skeptical Theory of Inheritance in Nonmonotonic Semantic Networks
 ARTIFICIAL INTELLIGENCE
, 1990
"... This paper describes a new approach to inheritance reasoning in semantic networks allowing for multiple inheritance with exceptions. The approach leads to an analysis of defeasible inheritance which is both welldefined and intuitively attractive: it yields unambiguous results applied to any acyclic ..."
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Cited by 115 (12 self)
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definitions when it is applied to nets about which our intuitions are unsettled, or in which different reasoning strategies could naturally be expected to yield distinct results. After exploring certain features of the definition presented here, we describe also a hybrid (parallelserial) algorithm
A nonmonotone GRASP
, 2014
"... A Greedy Randomized Adaptive Search Procedure (GRASP) is an iterative multistart metaheuristic for difficult combinatorial optimization problems. Each GRASP iteration consists of two phases: a construction phase, in which a feasible solution is produced, and a local search phase, in which a local o ..."
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solution is found. During this phase, starting from the current solution an improving neighbor solution is accepted and considered as new current solution. In this paper, we propose a variant of the GRASP framework that uses a new “nonmonotone” strategy to explore the neighborhood of the current solution
A nonmonotone semismooth inexact Newton method
"... In this work we propose a variant of the inexact Newton method for the solution of semismooth nonlinear systems of equations. We introduce a nonmonotone scheme, which couples the inexact features with the nonmonotone strategies. For the nonmonotone scheme, we present the convergence theorems. Finall ..."
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In this work we propose a variant of the inexact Newton method for the solution of semismooth nonlinear systems of equations. We introduce a nonmonotone scheme, which couples the inexact features with the nonmonotone strategies. For the nonmonotone scheme, we present the convergence theorems
Nonmonotonic feature selection
 In Proc. Intl. Conf. Machine Learning
"... Abstract We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinatorial optimization problem, and is usually solved by an approximation. Conventional feature selection methods add ..."
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Cited by 18 (2 self)
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selection. To this end, we develop an algorithm for nonmonotonic feature selection that approximates the related combinatorial optimization problem by a Multiple Kernel Learning (MKL) problem. We also present a strategy that derives a discrete solution from the approximate solution of MKL, and show
Nondeterministic, Nonmonotonic Logic Databases
"... We consider in this paper an extension of Datalog with mechanisms for temporal, nonmonotonic and nondeterministic reasoning, which we refer to as Datalog++. We show, by means of examples, its flexibility in expressing queries concerning aggregates and data cube. Also, we show how iterated fixpoint a ..."
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We consider in this paper an extension of Datalog with mechanisms for temporal, nonmonotonic and nondeterministic reasoning, which we refer to as Datalog++. We show, by means of examples, its flexibility in expressing queries concerning aggregates and data cube. Also, we show how iterated fixpoint
Results 1  10
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210