Some data come with missing values. For instance, a survey’s participant may ignore some questions. There is an abundant statistical literature on this topic, establishing for instance how to fit model without biases due to the missingness, and imputation strategies to provide practical solutions to the analyst. In machine learning, to build models that minimize a prediction risk, most work...
The question of texture synthesis in image processing is a very challenging problem that can be stated as followed: given an exemplar image, sample a new image that has the same statistical features (empirical mean, empirical covariance, filter responses, neural network responses, etc.). Exponential models then naturally arise as distributions satisfying these constraints in expectation while...
We will first discuss how deep learning techniques can be used for audio signals. To that aim, we will recall some of the important characteristics of an audio signal and review some of the main deep learning architectures and concepts used in audio signal analysis. We will then illustrate some of these concepts in more details with two applications, namely informed singing voice source...
