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Variant Grassmann Manifolds: A Representation Augmentation Method for Action Recognition

In classification tasks, classifiers trained with finite examples might generalize poorly to new data with unknown variance. For this issue, data augmentation is a successful solution where numerous artificial examples are added to training sets. In …

Short Sequence Classification Through Discriminable Linear Dynamical System

Linear dynamical system (LDS) offers a convenient way to reveal the unobservable structure behind the data. This makes it useful for data representation and explanatory analysis. An immediate limitation with this model is that most training …