# Engineering (engineering design, digital design)

Back## Cahiers du GERAD

### 214 results — page 2 of 11

PLSR1: A limited-memory partitioned quasi-Newton optimizer for partially-separable loss functions

Improving neural network optimizer convergence speed is a long-standing priority. Recently, there has been a focus on quasi-Newton optimization methods, whi...

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Historically, the training of deep artificial neural networks has relied on parallel computing to achieve practical effectiveness. However, with the increas...

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We introduce an iterative solver named MINARES for symmetric linear systems `\(Ax \approx b\)`

, where `\(A\)`

is possibly singular.
MINARES is based on t...

The indefinite proximal gradient method

We introduce a variant of the proximal gradient method in which the quadratic term is diagonal but may be indefinite, and is safeguarded by a trust region. ...

BibTeX referenceFluxNLPModels.jl and KnetNLPModels.jl: Connecting deep learning models with optimization solvers

This paper presents <code>FluxNLPModels.jl</code> and <code>KnetNLPModels.jl</code>, new Julia packages enabling a neural network, modelled with either Flux....

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We present a Julia framework dedicated to partially-separable problems whose element function are detected automatically. This framework takes advantage of ...

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This work considers stochastic optimization problems in which the objective function values can only be computed by a blackbox corrupted by some random noise...

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This paper first presents a time-series impact analysis of charging electric vehicles (EVs) to loading levels of power network equipment considering stochast...

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In this paper, we investigate the problem of system identification for autonomous Markov jump linear systems (MJS) with complete state observations. We prop...

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This paper presents `\(\texttt{Krylov.jl}\)`

, a Julia package that implements a collection of Krylov processes and methods for solving a variety of linear pr...

In multi-robot missions, relative position and attitude information between robots is valuable for a variety of tasks such as mapping, planning, and formatio...

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This note provides a counterexample to a theorem announced in the last part of the paper *Analysis of direct searches for discontinuous functions*, Mathemati...

Motivated by our collaboration with one of the largest fast-fashion retailers in Europe, we study a two-echelon inventory control problem called the One-Ware...

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This paper presents PDENLPModels.jl a new Julia package for modeling and discretizing optimization problems with mixed algebraic and partial differential equ...

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Providing the right data to a machine learning model is an important step to insure the performance of the model. Non-compliant training data instances may l...

BibTeX referenceOn GSOR, the generalized successive overrelaxation method for double saddle-point problems

We consider the generalized successive overrelaxation (GSOR) method for solving a class of block three-by-three saddle-point problems. Based on the necessary...

BibTeX referenceOptimal localizability criterion for positioning with distance-deteriorated relative measurements

Position estimation in Multi-Robot Systems (MRS) relies on relative angle or distance measurements between the robots, which generally deteriorate as dista...

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We consider the problem of training a deep neural network with nonsmooth regularization to retrieve a sparse and efficient sub-structure. Our regularizer is ...

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The conjugate gradient (CG) method is a classic Krylov subspace method for solving symmetric positive definite linear systems. We introduce an analogous sem...

BibTeX referenceComputing a sparse projection into a box

We describe a procedure to compute a projection of `\(w \in ℝ^n\)`

into the intersection of the so-called *zero-norm* ball `\(k B_0\)`

of radius `\(k\)`

, i....