Jean-Pierre Dussault
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In this paper, we compare the BFGS and the conjugate gradient (CG) methods for solving unconstrained problems with a trust-region algorithm. The main result ...
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This paper targets a stochastic energy management problem. We first decouple the stochasticity of the global scenarios to local scenarios. Then, we use spat...
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In Positron Emission Tomography (PET), deep crystals (>20 mm) must be used to enhance detection efficiency and increase overall scanner sensitivity. Howeve...
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Positron emission tomography (PET) image reconstruction in the presence of periodic motion, such as heartbeat and breathing, has been actively investigated ...
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Adaptative cubic regularization (ARC) methods for unconstrained optimization compute steps from linear systems with a shifted Hessian in the spirit of the mo...
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In this work, we examine how to combine the score function method with the standard crude Monte Carlo and experimental design approaches, in order to evalua...
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It is well-known (see Pang and Chan [7]) that Newton's method, applied to strongly monotone variational inequalities, is locally and quadratically convergent...
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Applied to strongly monotone variational inequality problems, Newton's algorithm achieves local quadratic convergence. However, global convergence cannot be...
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