We present a simple method for transferring dependency parsers from source languages with labeled training data to target languages without labeled training data. We first demons...
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization sys...