CLAIRE makes machine translation BLEU no more

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 133-139).We introduce CLAIRE, a mathematically principled model for inferring ranks and scores for arbitrary items based on forced-choice binary comparisons, and show how to apply this technique to statistical models to take advantage of problem-specific assistance from non-experts. We apply this technique to two language processing problems: parsing and machine translation. This leads to an analysis which casts doubts on modern evaluation methods for machine translation systems, and an application of CLAIRE as a new technique for evaluating machine translation systems which is inexpensive, has theoretical guarantees, and correlates strongly in practice with more expensive human judgments of system quality. Our analysis reverses several major tenants of the mainstream machine translation research agenda, suggesting in particular that the use of linguistic models should be reexamined.by Ali Mohammad.Sc.D

Low-Resource Unsupervised NMT:Diagnosing the Problem and Providing a Linguistically Motivated Solution

Unsupervised Machine Translation hasbeen advancing our ability to translatewithout parallel data, but state-of-the-artmethods assume an abundance of mono-lingual data. This paper investigates thescenario where monolingual data is lim-ited as well, finding that current unsuper-vised methods suffer in performance un-der this stricter setting. We find that theperformance loss originates from the poorquality of the pretrained monolingual em-beddings, and we propose using linguis-tic information in the embedding train-ing scheme. To support this, we look attwo linguistic features that may help im-prove alignment quality: dependency in-formation and sub-word information. Us-ing dependency-based embeddings resultsin a complementary word representationwhich offers a boost in performance ofaround 1.5 BLEU points compared to stan-dardWORD2VECwhen monolingual datais limited to 1 million sentences per lan-guage. We also find that the inclusion ofsub-word information is crucial to improv-ing the quality of the embedding

Extracellular Matrix in Development and Disease

The extracellular matrix in development and disease deals with the molecular and cellular aspects of development and disease. Cells exist in three-dimensional scaffolding called the extracellular matrix. The matrix holds together the millions of cells that make up our blood vessels, organs, skin, and all tissues of the body. The matrix serves as a reservoir of signaling molecules as well. In bacterial cultures, biofilms form as an extracellular matrix and play essential roles in disease and drug resistance. Topics such as matrix structure and function, cell attachment and cell surface proteins mediating cell-matrix interactions, synthesis, regulation, composition, structure, assembly, remodeling, and function of the matrix are included. A common thread uniting the topics is the essential nature that the matrix plays in normal development and pathophysiology. Providing new knowledge will lead us to improved diagnostics, the preventions of disease progression, and therapeutic strategies for the repair and regeneration of tissues. Topics such as the extracellular matrix in hereditary diseases, reproduction, cancer, muscle, and tissue engineering applications, and diverse roles for integrins, are included in this collection