Tera-Scale Translation Models via Pattern Matching

Title of Dissertation: Machine Translation by Pattern Matching Machine Translation by Pattern Matching

Title of dissertation: MACHINE TRANSLATION BY PATTERN MATCHING Adam Lopez, Doctor of Philosophy, 2008 Dissertation directed by: Professor Philip Resnik Department of Linguistics and Institute for Advanced Computer Studies The best systems for machine translation of natural language are based on statistical models learned from data. Conventional representation of a statistical translation model ...

Acoustic Source Localization via Distributed Sensor Networks using Tera-scale Optical-Core Devices

Runtime Environment for Tera-scale Platforms

This paper presents the design and implementation of a runtime environment for tera-scale platforms. System software stacks currently view tera-scale platforms as an “SMP (symmetric multiprocessor) on a die.” We show that there are fundamental differences between tera-scale and SMP systems that require that the software (SW) stack be re-architected. In particular, the SW stack needs to provide ...

General Stereo Image Matching Using Symmetric Complex Wavelets

General stereo image matching provides an adequate but hard problem with suucient complexity, with which the potential of wavelets may be exploited to a full extent. An ideal stereo image matching algorithm is supposed to be invariant to the scale, translation, rotation, and partial correspondence between two given stereo images. While the multiresolution of wavelets is good at scale adaptivity...

Unnesting of Copatterns

Inductive data such as finite lists and trees can elegantly be defined by constructors which allow programmers to analyze and manipulate finite data via pattern matching. Dually, coinductive data such as streams can be defined by observations such as head and tail and programmers can synthesize infinite data via copattern matching. This leads to a symmetric language where finite and infinite da...