Data-driven learning based on shift reduce parsing algorithms has emerged dependency parsing and shown excellent performance to many Treebanks. In this paper, we investigate the e...
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
This paper describes a new finite-state shallow parser. It merges constructive and reductionist approaches within a highly modular architecture. Syntactic information is added at ...
In the discrete filtering problem, a data sequence over a finite alphabet is assumed to be corrupted by a discrete memoryless channel. The goal is to reconstruct the clean sequenc...
Erik Ordentlich, Tsachy Weissman, Marcelo J. Weinb...
Language comprehension in humans is significantly constrained by memory, yet rapid, highly incremental, and capable of utilizing a wide range of contextual information to resolve ...
Roger P. Levy, Florencia Reali, Thomas L. Griffith...