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On semi-supervised learning
(Springer, 2020-12)
Major efforts have been made, mostly in the machine learning literature, to construct good predictors combining unlabelled and labelled data. These methods are known as semi-supervised. They deal with the problem of how ...
Learning latent jet structure
(Multidisciplinary Digital Publishing Institute, 2021-06-29)
We summarize our recent work on how to infer on jet formation processes directly from substructure data using generative statistical models. We recount in detail how to cast jet substructure observables’ measurements in ...
Quality flaw prediction in spanish Wikipedia: A case of study with verifiability flaws
(Pergamon-Elsevier Science Ltd, 2018-11)
In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated ...
Using the Web as corpus for self-training text categorization
(Springer Science+Business Media, 2009)
Using the Web as corpus for self-training text categorization
(Springer Science+Business Media, 2009)
A semi-supervised incremental algorithm to automatically formulate topical queries
(Elsevier Science Inc, 2009-05)
The quality of the material collected by a context-based Web search systems is highly dependant on the vocabulary used to generate the search queries. This paper proposes to apply a semi-supervised algorithm to incrementally ...
Semi-supervised 3D object recognition through CNN labeling
(04/01/2018)
Despite the outstanding results of Convolutional Neural Networks (CNNs) in object recognition and classification, there are still some open problems to address when applying these solutions to real-world problems. Specifically, ...