Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
We have previously shown how the discovery of classes from objects can be automated, and how the resulting class organization can be e ciently optimized in the case where the opti...
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
We present a new method for segmenting actions into primitives and classifying them into a hierarchy of action classes. Our scheme learns action classes in an unsupervised manner ...