We propose a class of preconditioners for large positive definite linear systems, arising in nonlinear optimization frameworks. These preconditioners can be computed as by-product of Krylov-subspace solvers. Preconditioners in our class are chosen by setting the values of some user-dependent...
Nonlinear Optimization
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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)...