10 citations · 24 across the 8 of their papers we have counts for
8 papers
HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM
Kazuki Kawamura, Akihiro Yamamoto
In this paper, we propose a novel method for extracting information from HTML tables with similar contents but with a different structure. We aim to integrate multiple HTML tables…
Differentiable Inductive Logic Programming for Structured Examples
Hikaru Shindo, Masaaki Nishino, Akihiro Yamamoto
The differentiable implementation of logic yields a seamless combination of symbolic reasoning and deep neural networks. Recent research, which has developed a differentiable frame…
Metric Learning for Ordered Labeled Trees with pq-grams
Hikaru Shindo, Masaaki Nishino, Yasuaki Kobayashi +1
Computing the similarity between two data points plays a vital role in many machine learning algorithms. Metric learning has the aim of learning a good metric automatically from da…
Algorithms and Hardness Results for the Maximum Balanced Connected Subgraph Problem
Yasuaki Kobayashi, Kensuke Kojima, Norihide Matsubara +2
The Balanced Connected Subgraph problem (BCS) was recently introduced by Bhore et al. (CALDAM 2019). In this problem, we are given a graph whose vertices are colored by red or…
Automatic Source Code Summarization with Extended Tree-LSTM
Yusuke Shido, Yasuaki Kobayashi, Akihiro Yamamoto +2
Neural machine translation models are used to automatically generate a document from given source code since this can be regarded as a machine translation task. Source code summari…
Improved Methods for Computing Distances between Unordered Trees Using Integer Programming
Eunpyeong Hong, Yasuaki Kobayashi, Akihiro Yamamoto
Kondo et al. (DS 2014) proposed methods for computing distances between unordered rooted trees by transforming an instance of the distance computing problem into an instance of the…
Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM
Takanori Inazumi, Takashi Washio, Shohei Shimizu +3
Discovering causal relations among observed variables in a given data set is a major objective in studies of statistics and artificial intelligence. Recently, some techniques to di…
Discovering causal structures in binary exclusive-or skew acyclic models
Takanori Inazumi, Takashi Washio, Shohei Shimizu +3
Discovering causal relations among observed variables in a given data set is a main topic in studies of statistics and artificial intelligence. Recently, some techniques to discove…