We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
This paper describes an empirical study of high-performance dependency parsers based on a semi-supervised learning approach. We describe an extension of semisupervised structured ...
Jun Suzuki, Hideki Isozaki, Xavier Carreras, Micha...
The concept of Dynamic Neural Networks (DNN) is a new approach within the Neural Network paradigm, which is based on the dynamic construction of Neural Networks during the processi...
: This paper presents an online learning framework for the behavior of an articulated body by capturing its motion using real-time video. In our proposed framework, supervised lear...
Abstract. We introduce LTAG-spinal, a novel variant of traditional Lexicalized Tree Adjoining Grammar (LTAG) with desirable linguistic, computational and statistical properties. Un...