Domain Adaptation for Neural Networks by Parameter Augmentation

We propose a simple domain adaptation method for neural networks in a supervised setting. Supervised domain adaptation is a way of improving the generalization performance on the target domain by using the source domain dataset, assuming that both of the datasets are labeled. Recently, recurrent neural networks have been shown to be successful on a variety of NLP tasks such as caption generation; however, the existing domain adaptation techniques are limited to (1) tune the model parameters by the target dataset after the training by the source dataset, or (2) design the network to have dual output, one for the source domain and the other for the target domain. Reformulating the idea of the domain adaptation technique proposed by Daume (2007), we propose a simple domain adaptation method, which can be applied to neural networks trained with a cross-entropy loss. On captioning datasets, we show performance improvements over other domain adaptation methods.Comment: 9 page. To appear in the first ACL Workshop on Representation Learning for NL

Detection of CO(J=1-0) Emission from Barred Spiral Galaxies at z~0.1

We present the results of CO (J=1-0) observations towards nine barred spiral galaxies at z=0.08-0.25 using the 45-m telescope at Nobeyama Radio Observatory (NRO). This survey is the first one specialized for barred spiral galaxies in this redshift range. We detected CO emission from six out of nine galaxies, whose CO luminosity (L_CO') ranges (1.09-10.8)\times10^9 K km s^{-1} pc^2. These are the infrared (IR) dimmest galaxies that have ever been detected in CO at z~0.1 to date. They follow the L_CO'-L_IR relation among local spiral galaxies, Luminous Infrared Galaxies (LIRGs), Ultra-Luminous Infrared Galaxies (ULIRGs) and Sub-millimeter Galaxies (SMGs). Their L_CO' and L_IR are higher than that of local spiral galaxies which have been detected in CO so far, and L_IR/L'_CO, which is a measure of star formation efficiency, is comparable to or slightly higher than that of local ones. This result suggests that these galaxies are forming stars more actively than local spirals galaxies simply because they have more fuel.Comment: 9 pages, 5 figures, accepted for publication in PAS

Coordinate transformation formulation of electromagnetic scattering from imperfectly periodic surfaces

This paper considers the electromagnetic scattering problem of periodically corrugated surface with local imperfection of structural periodicity, and presents a formulation based on the coordinate transformation method (C-method). The C-method is originally developed to analyze the plane-wave scattering from perfectly periodic structures, and uses the pseudo-periodic property of the fields. The fields in imperfectly periodic structures are not pseudo-periodic and the C-method cannot be directly applied. This paper introduces the pseudo-periodic Fourier transform to convert the fields in imperfectly periodic structures to pseudo-periodic ones, and the C-method becomes then applicable.Web of Science2099990997