• Hadamard Product for Low-rank Bilinear Pooling

    WHY? Bilinear model can caputure rich relation of two vectors. However, the computational complexity of bilinear model is huge due to its high dimensionality. To make bilinear model more applicable, this paper suggests low-rank bilinear pooling using Hadamard product. WHAT? Bilinear model have huge matrix W of N x M....


  • Stacked Attention Networks for Image Question Answering

    WHY? Visual question answering task is answering natural language questions based on images. To solve questions that require multi-step reasoning, stacked attention networks(SANs) stacks several layers of attention on parts of images based on query. WHAT? Image model extracts feature map from image with VGGNet structure. Question model uses the...


  • Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing

    Summary Resilient Distributed Datasets(RDD) is a distributed memory abstraction to perform in-memory computations of large clusters. While many data-processing algorithms are applied to data iteratively, the reuse of intermediate results are rarely exploited. To enable in-memory processing with fault-tolerence, RDD provide an interface based on coarse-grained transformation while logging the...


  • The Hadoop Distributed File System

    Summary Hadoop Distributed File System(HDFS) construct file system in cluster level. Huge amount of data are stored in distributed servers and enable users to access with high bandwith. Just like UNIX file system, HDFS keep metadata for data it stores. A dedicated server that stores metadata is called NameNode, and...


  • Multimodal Residual Learning for Visual QA

    WHY? Visual question answering task is to answer to natural language question based on images requiring extraction of information from both images and texts. Stacked Attention Networks(SAN) stacked several layers of attention to answer to complicated questions that requires reasoning. Multimodal Residual Network (MRN) points out weighted averaging of attention...