A greedy randomized adaptive search procedure (GRASP) is an itera-
tive 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...
Nonlinear Optimization
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Our recently developed Reverse Priority (RP) redundancy resolution method is extended here to the presence of unilateral constraints. The RP method computes the solution to a stack of prioritized tasks starting from the lowest priority one, and adding iteratively the contributions of higher...
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In this paper, we deal with matrix-free preconditioners for nonlinear conjugate gradient (NCG) methods. In particular, we review proposals based on quasi-Newton updates, and either satisfying the secant equation or a secant-like equation at some of the previous iterates. Conditions are given...
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Speaker: Tommaso Colombo
Title: Recurrent Neural Networks: why do LSTM networks perform so well in time series prediction?
(Joint work with: Alberto De Santis, Stefano Lucidi)
Abstract:
Long Short-Term Memory (LSTM)...