The aim of this paper is to give an overview of domain adaptation and transfer learning with
a specific view on visual applications. After a general motivation, we first position domain …

While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

In machine learning, if the training data is an unbiased sample of an underlying distribution,
then the learned classification function will make accurate predictions for new samples …

With the availability of speech data obtained from different devices and varied acquisition
conditions, we are often faced with scenarios, where the intrinsic discrepancy between the …

In many practical transfer learning scenarios, the feature distribution is different across the
source and target domains (ie, nonindependent identical distribution). Maximum mean …

One of the serious obstacles to the applications of speech emotion recognition systems in
real-life settings is the lack of generalization of the emotion classifiers. Many recognition …

We propose a new statistical approach to the problem of inlier-based outlier detection, ie,
finding outliers in the test set based on the training set consisting only of inliers. Our key idea …

As a promising area in artificial intelligence, a new learning paradigm, called Small Sample
Learning (SSL), has been attracting prominent research attention in the recent years. In this …

Many learning situations involve learning the conditional distribution p (y| x) when the
training instances are drawn from the training distribution p_tr (x), even though it will later be …

We consider the problem of learning a classifier using only positive and unlabeled samples.
In this setting, it is known that a classifier can be successfully learned if the class prior is …