Sort by
Refine Your Search
-
Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 12 days ago
the training. This approach has multiple benefits. First, there is no need to store and move a huge pre-created data set: float matrices of data can take terrabytes of memory, and reading them from the disk
-
Laboratoire National de Métrologie et d'Essais - LNE | Paris 15, le de France | France | about 1 month ago
on the primary data. They are often captured from multiple scans made from different locations to unspecified surface locations. This introduces novel sources of uncertainty while potentially reducing the impact
-
well as in the design of machine learning algorithms (ANN, SVM, Decision Tree, and Random Forest) applied to healthcare, will be particularly valued. Proficiency in programming tools (Matlab) and statistical
-
minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
-
" setting [4], where the benchmark is the optimal online algorithm rather than the expected maximum, making the competition more dynamic. - Study settings where multiple items are allocated to buyers, such as
-
, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
-
train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
-
combining multiple ML models have been explored to optimise predictions, enabling algorithms to collaborate and achieve better results. Ensemble methods, in particular, have demonstrated superior performance
-
. Indeed, when multiple sources exist in the vicinity of a same sensing unit, their signatures mix and estimation of individual sources is disturbed by the other co-occurring sources. The aim of the doctoral
-
analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and