Literatura científica selecionada sobre o tema "Selection et optimisation d'hyperparamètre"
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Artigos de revistas sobre o assunto "Selection et optimisation d'hyperparamètre"
Grandjean, Martine, Thomas Meyer, Cédric Haon e Pascale Chenevier. "Selection and Optimisation of Silicon Anodes for All-Solid-State Batteries". ECS Meeting Abstracts MA2022-01, n.º 2 (7 de julho de 2022): 408. http://dx.doi.org/10.1149/ma2022-012408mtgabs.
Texto completo da fonteAvendaño, S., B. Villanueva e J. A. Woolliams. "Optimisation of selection decisions in the UK Meatlinc breed of sheep". Proceedings of the British Society of Animal Science 2002 (2002): 194. http://dx.doi.org/10.1017/s1752756200008504.
Texto completo da fonteVillanueva, B., R. Pong-Wong e J. A. Woolliams. "Benefits from marker assisted selection with optimised contributions and prior information on the QTL effect". Proceedings of the British Society of Animal Science 2002 (2002): 57. http://dx.doi.org/10.1017/s1752756200007134.
Texto completo da fonteHoos, Holger. "Computer-Aided Algorithm Design: Automated Tuning, Configuration, Selection, and Beyond". Proceedings of the International Conference on Automated Planning and Scheduling 20 (25 de maio de 2021): 268–69. http://dx.doi.org/10.1609/icaps.v20i1.13426.
Texto completo da fonteSaeed, D., G. Carter e C. Parsons. "A systematic review of interventions to improve medicines optimisation in frail older patients in secondary and acute care settings". International Journal of Pharmacy Practice 29, Supplement_1 (26 de março de 2021): i22—i23. http://dx.doi.org/10.1093/ijpp/riab015.026.
Texto completo da fonteGarba, Issa, Zakari Seybou Abdourahamane, Abdou Amadou Sanoussi e Illa Salifou. "Optimisation de l'Evaluation de la Biomasse Fourragère en Zone Sahélienne Grâce à l’Utilisation de la Méthode de Régression Linéaire Multiple en Conjonction Avec la Stratification". European Scientific Journal, ESJ 19, n.º 33 (30 de novembro de 2023): 52. http://dx.doi.org/10.19044/esj.2023.v19n33p52.
Texto completo da fonteMiraftab, Mohsen, Ian Rushforth e Kirill Horoshenkov. "ACOUSTIC UNDERLAY MANUFACTURED FROM CARPET TILE WASTES". AUTEX Research Journal 6, n.º 1 (1 de março de 2006): 49–58. http://dx.doi.org/10.1515/aut-2006-060107.
Texto completo da fontePodolská, K., D. Mazánková e M. Göböová. "Retrospective Assessment of the Use of Pharmacotherapeutic Agents in Pregnancy with Potential Impact on Neonatal Health". European Pharmaceutical Journal 69, n.º 2 (1 de agosto de 2022): 17–25. http://dx.doi.org/10.2478/afpuc-2022-0015.
Texto completo da fonteMccallum, C., M. Campbell, J. Vines, T. Rapley e K. Hackett. "SAT0614-HPR IDENTIFYING AND OPTIMISING MULTIPLE INTERVENTION COMPONENTS AND THEIR DELIVERY WITHIN A SELF-MANAGEMENT SMARTPHONE APP FOR PEOPLE WITH SJÖGREN’S SYNDROME: A QUALITATIVE STUDY". Annals of the Rheumatic Diseases 79, Suppl 1 (junho de 2020): 1267.1–1268. http://dx.doi.org/10.1136/annrheumdis-2020-eular.2283.
Texto completo da fontePilewicz, PhD Tomasz, e Wojciech Sabat. "Behavioural location theory – evolution, tools and future". Kwartalnik Nauk o Przedsiębiorstwie 46, n.º 1 (15 de março de 2018): 61–68. http://dx.doi.org/10.5604/01.3001.0012.0998.
Texto completo da fonteTeses / dissertações sobre o assunto "Selection et optimisation d'hyperparamètre"
Bertrand, Quentin. "Hyperparameter selection for high dimensional sparse learning : application to neuroimaging". Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG054.
Texto completo da fonteDue to non-invasiveness and excellent time resolution, magneto- and electroencephalography (M/EEG) have emerged as tools of choice to monitor brain activity. Reconstructing brain signals from M/EEG measurements can be cast as a high dimensional ill-posed inverse problem. Typical estimators of brain signals involve challenging optimization problems, composed of the sum of a data-fidelity term, and a sparsity promoting term. Because of their notoriously hard to tune regularization hyperparameters, sparsity-based estimators are currently not massively used by practitioners. The goal of this thesis is to provide a simple, fast, and automatic way to calibrate sparse linear models. We first study some properties of coordinate descent: model identification, local linear convergence, and acceleration. Relying on Anderson extrapolation schemes, we propose an effective way to speed up coordinate descent in theory and practice. We then explore a statistical approach to set the regularization parameter of Lasso-type problems. A closed-form formula can be derived for the optimal regularization parameter of L1 penalized linear regressions. Unfortunately, it relies on the true noise level, unknown in practice. To remove this dependency, one can resort to estimators for which the regularization parameter does not depend on the noise level. However, they require to solve challenging "nonsmooth + nonsmooth" optimization problems. We show that partial smoothing preserves their statistical properties and we propose an application to M/EEG source localization problems. Finally we investigate hyperparameter optimization, encompassing held-out or cross-validation hyperparameter selection. It requires tackling bilevel optimization with nonsmooth inner problems. Such problems are canonically solved using zeros order techniques, such as grid-search or random-search. We present an efficient technique to solve these challenging bilevel optimization problems using first-order methods
YACOUB, MEZIANE. "Selection de caracteristiques et optimisation d'architectures dans les systemes d'apprentissage connexionnistes". Paris 13, 1999. http://www.theses.fr/1999PA132014.
Texto completo da fontePURBA, ABDUL RAZAK. "Optimisation de la selection recurrente reciproque du palmier a huile (elaeis guineensis jacq. ) par l'utilisation conjointe des index de selection et des marqueurs moleculaires". Montpellier, ENSA, 2000. http://www.theses.fr/2000ENSA0018.
Texto completo da fonteSarmis, Merdan. "Etude de l'activité neuronale : optimisation du temps de simulation et stabilité des modèles". Thesis, Mulhouse, 2013. http://www.theses.fr/2013MULH3848/document.
Texto completo da fonteComputational Neuroscience consists in studying the nervous system through modeling and simulation. It is to characterize the laws of biology by using mathematical models integrating all known experimental data. From a practical point of view, the more realistic the model, the largest the required computational resources. The issue of complexity and accuracy is a well known problem in the modeling and identification of models. The research conducted in this thesis aims at improving the simulation of mathematical models representing the physical and chemical behavior of synaptic receptors. Models of synaptic receptors are described by ordinary differential equations (ODE), and are resolved with numerical procedures. In order to optimize the performance of the simulations, I have implemented various ODE numerical resolution methods. To facilitate the selection of the best solver, a method, requiring a minimum amount of information, has been proposed. This method allows choosing the best solver in order to optimize the simulation. The method demonstrates that the dynamic of a model has greater influence on the solver performances than the kinetic scheme of the model. In addition, to characterize pathogenic behavior, a parameter optimization is performed. However, some parameter values lead to unstable models. A stability study allowed for determining the stability of the models with parameters provided by the literature, but also to trace the stability constraints depending to these parameters. Compliance with these constraints ensures the stability of the models studied during the optimization phase, and therefore the success of the procedure to study pathogen models
Rincent, Renaud. "Optimisation des stratégies de génétique d'association et de sélection génomique pour des populations de diversité variable : Application au maïs". Thesis, Paris, AgroParisTech, 2014. http://www.theses.fr/2014AGPT0018/document.
Texto completo da fonteMajor progresses have been achieved in genotyping technologies, which makes it easier to decipher the relationship between genotype and phenotype. This contributed to the understanding of the genetic architecture of traits (Genome Wide Association Studies, GWAS), and to better predictions of genetic value to improve breeding efficiency (Genomic Selection, GS). The objective of this thesis was to define efficient ways of leading these approaches. We first derived analytically the power from classical GWAS mixed model and showed that it was lower for markers with a small minimum allele frequency, a strong differentiation among population subgroups and that are strongly correlated with markers used for estimating the kinship matrix K. We considered therefore two alternative estimators of K. Simulations showed that these were as efficient as classical estimators to control false positive and provided more power. We confirmed these results on true datasets collected on two maize panels, and could increase by up to 40% the number of detected associations. These panels, genotyped with a 50k SNP-array and phenotyped for flowering and biomass traits, were used to characterize the diversity of Dent and Flint groups and detect QTLs. In GS, studies highlighted the importance of relationship between the calibration set (CS) and the predicted set on the accuracy of predictions. Considering low present genotyping cost, we proposed a sampling algorithm of the CS based on the G-BLUP model, which resulted in higher accuracies than other sampling strategies for all the traits considered. It could reach the same accuracy than a randomly sampled CS with half of the phenotyping effort
Blanc, Guylaine. "Selection assistee par marqueurs (sam) dans un dispositif multiparental connecte - application au maÏs et approche par simulations". Phd thesis, INAPG (AgroParisTech), 2006. http://pastel.archives-ouvertes.fr/pastel-00003478.
Texto completo da fonteHamdi, Faiza. "Optimisation et planification de l'approvisionnement en présence du risque de rupture des fournisseurs". Thesis, Ecole nationale des Mines d'Albi-Carmaux, 2017. http://www.theses.fr/2017EMAC0002/document.
Texto completo da fonteTrade liberalization, the development of mean of transport and the development economic of emerging countries which lead to globalization of supply chain is irreversible phenomen. They can reduce costs, in return, they multiply the risk of disruption from upstream stage to downstream stage. In this thesis, we focus on the inbound supply chain stage. We treat more specifically the case of a purchasing central to select suppliers and allocate the orders. Each of the suppliers cannot deliver its orders due to internal reasons (poor quality problems) or external reasons (natural disasters, transport problems). According to the selected suppliers deliver their orders or not, the transaction operation will generate a profit or loss. The objective of this thesis is to provide decision support tools to a decision maker faced with this problem by taking into account the behavior of decision maker toward risk. We proposed stochastic mixed integer linear programs to model this problem. In the first part, we focuses on the development of a decision support visual tool that allows a decision maker to find a compromise between maximizing the expected profit and minimize the risk of loss. In the second part, we integrated the techniques of estimation of risk VaR and CVaR in this problem. The objective is to help decision maker to minimize the expected cost and minimize the conditional value at risk simultanously via calculating of VaR. Result shows that the decision maker must tack into account the different scenarios of disruption regardless their probability of realisation
Landru, Didier. "Aides informatisées à la selection des matériaux et des procédés dans la conception des pièces de structure". Grenoble INPG, 2000. http://www.theses.fr/2000INPG0012.
Texto completo da fonteAkkouche, Nourredine. "Optimisation du test de production de circuits analogiques et RF par des techniques de modélisation statistique". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00625469.
Texto completo da fontePham, Viet Nga. "Programmation DC et DCA pour l'optimisation non convexe/optimisation globale en variables mixtes entières : Codes et Applications". Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00833570.
Texto completo da fonte