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
-
-
We consider the convex quadratic linearly constrained problem with bounded variables and with huge and dense Hessian matrix that arises in many applications such as the training problem of bias support vector machines. We propose a decomposition algorithmic scheme suitable to parallel...
-
-
-
In this paper we propose the use of damped techniques within Nonlinear Conjugate Gradient (NCG) methods. Damped techniques were introduced by Powell and recently reproposed by Al-Baali and till now, only applied in the framework of quasi--Newton methods. We extend their use to NCG methods in large...
-
-
-
-
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)...