Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning

Recently there has been a lot of interest in learning common representations for multiple views of data. Typically, such common representations are learned using a parallel corpus between the two views (say, 1M images and their English captions). In this work, we address a real-world scenario where no direct parallel data is available between two views of interest (say, $V_1$ and $V_2$) but parallel data is available between each of these views and a pivot view ($V_3$). We propose a model for learning a common representation for $V_1$, $V_2$ and $V_3$ using only the parallel data available between $V_1V_3$ and $V_2V_3$. The proposed model is generic and even works when there are $n$ views of interest and only one pivot view which acts as a bridge between them. There are two specific downstream applications that we focus on (i) transfer learning between languages $L_1$,$L_2$,...,$L_n$ using a pivot language $L$ and (ii) cross modal access between images and a language $L_1$ using a pivot language $L_2$. Our model achieves state-of-the-art performance in multilingual document classification on the publicly available multilingual TED corpus and promising results in multilingual multimodal retrieval on a new dataset created and released as a part of this work.Comment: Published at NAACL-HLT 201

Data Envelopment Analysis (Dea) approach In efficiency transport manufacturing industry in Malaysia

The objective of this study was to measure of technical efficiency, transport manufacturing industry in Malaysia score using the data envelopment analysis (DEA) from 2005 to 2010. The efficiency score analysis used only two inputs, i.e., capital and labor and one output i.e., total of sales. The results shown that the average efficiency score of the Banker, Charnes, Cooper - Variable Returns to Scale (BCC-VRS) model is higher than the Charnes, Cooper, Rhodes - Constant Return to Scale (CCR-CRS) model. Based on the BCC-VRS model, the average efficiency score was at a moderate level and only four sub-industry that recorded an average efficiency score more than 0.50 percent during the period study. The implication of this result suggests that the transport manufacturing industry needs to increase investment, especially in human capital such as employee training, increase communication expenses such as ICT and carry out joint ventures as well as research and development activities to enhance industry efficiency

The Simplest Evaluation Measures for XML Information Retrieval that Could Possibly Work

This paper reviews several evaluation measures developed for evaluating XML information retrieval (IR) systems. We argue that these measures, some of which are currently in use by the INitiative for the Evaluation of XML Retrieval (INEX), are complicated, hard to understand, and hard to explain to users of XML IR systems. To show the value of keeping things simple, we report alternative evaluation results of official evaluation runs submitted to INEX 2004 using simple metrics, and show its value for INEX

Regular decomposition of large graphs and other structures: scalability and robustness towards missing data

A method for compression of large graphs and matrices to a block structure is further developed. Szemer\'edi's regularity lemma is used as a generic motivation of the significance of stochastic block models. Another ingredient of the method is Rissanen's minimum description length principle (MDL). We continue our previous work on the subject, considering cases of missing data and scaling of algorithms to extremely large size of graphs. In this way it would be possible to find out a large scale structure of a huge graphs of certain type using only a tiny part of graph information and obtaining a compact representation of such graphs useful in computations and visualization.Comment: Accepted for publication in: Fourth International Workshop on High Performance Big Graph Data Management, Analysis, and Mining, December 11, 2017, Bosto U.S.