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...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Saving internal program data for further use is one of the most useful ideas in programming. Developing general features to provide such data saving/ restoring is a very active res...
Abstract. Character design is a key ingredient to the success of any comicbook, graphic novel, or animated feature. Artists typically use shape, size and proportion as the first de...
Md. Tanvirul Islam, Kaiser Md. Nahiduzzaman, Why Y...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...