64,101 research outputs found
Cross-Lingual Adaptation using Structural Correspondence Learning
Cross-lingual adaptation, a special case of domain adaptation, refers to the
transfer of classification knowledge between two languages. In this article we
describe an extension of Structural Correspondence Learning (SCL), a recently
proposed algorithm for domain adaptation, for cross-lingual adaptation. The
proposed method uses unlabeled documents from both languages, along with a word
translation oracle, to induce cross-lingual feature correspondences. From these
correspondences a cross-lingual representation is created that enables the
transfer of classification knowledge from the source to the target language.
The main advantages of this approach over other approaches are its resource
efficiency and task specificity.
We conduct experiments in the area of cross-language topic and sentiment
classification involving English as source language and German, French, and
Japanese as target languages. The results show a significant improvement of the
proposed method over a machine translation baseline, reducing the relative
error due to cross-lingual adaptation by an average of 30% (topic
classification) and 59% (sentiment classification). We further report on
empirical analyses that reveal insights into the use of unlabeled data, the
sensitivity with respect to important hyperparameters, and the nature of the
induced cross-lingual correspondences
Compensation for the setup instability in ptychographic imaging
The high-frequency vibration of the imaging system degrades the quality of
the reconstruction of ptychography by acting as a low-pass filter on ideal
diffraction patterns. In this study, we demonstrate that by subtracting the
deliberately blurred diffraction patterns from the recorded patterns and adding
the properly amplified subtraction to the original data, the high-frequency
components lost by the vibration of the setup can be recovered, and thus the
image quality can be distinctly improved. Because no prior knowledge regarding
the vibrating properties of the imaging system is needed, the proposed method
is general and simple and has applications in several research fields.Comment: 13pages, 10figure
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