This paper describes an unsupervised algorithm for segmenting categorical time series. The algorithm first collects statistics about the frequency and boundary entropy of ngrams, t...
Autonomous systems which learn and utilize a limited
visual vocabulary have wide spread applications.
Enabling such systems to segment a set of cluttered scenes
into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...
This paper describes an unsupervised algorithm for segmenting categorical time series into episodes. The VOTING-EXPERTS algorithm first collects statistics about the frequency an...
In this paper, we consider facial expression recognition using an unsupervised learning framework. Specifically, given a data set composed of a number of facial images of the same...
Behnood Gholami, Wassim M. Haddad, Allen Tannenbau...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...