Explanipedia

Hilbert Forest in the SISAP 2025 Indexing Challenge Open

Yasunobu Imamura, Takeshi Shinohara, Naoya Higuchi, Kouichi Hirata, Tetsuji Kuboyama · 2025

We report our participation in the SISAP 2025 Indexing Challenge using a novel indexing technique called the Hilbert forest. The method is based on the fast Hilbert sort algorithm, which efficiently orders high-dimensional points along a H…

Exploration of Stable Atomic Configurations in Graphene-like BCN Systems by Density Functional Theory and Bayesian Optimization Open

Takeshi Hara, Akira Kusaba, Yoshihiro Kangawa, Tetsuji Kuboyama, David R. Bowler , et al. · 2025

h-BCN is an intriguing material system where the bandgap varies considerably depending on the atomic configuration, even at a fixed composition. Exploring stable atomic configurations in this system is crucial for discussing the energetic …

Fast Filtering for Similarity Search Using Conjunctive Enumeration of Sketches in Order of Hamming Distance Open

Naoya Higuchi, Yasunobu Imamura, Vladimír Míč, Takeshi Shinohara, Kouichi Hirata , et al. · 2024

Sketches are compact bit-string representations of points, often employed for speeding up searches through the effects of dimensionality reduction and data compression. In this paper, we propose a novel sketch enumeration method and demons…

Beyond <i>ab initio</i> reaction simulator: An application to GaN metalorganic vapor phase epitaxy Open

Akira Kusaba, Shugo Nitta, Kenji Shiraishi, Tetsuji Kuboyama, Yoshihiro Kangawa · 2022

To develop a quantitative reaction simulator, data assimilation was performed using high-resolution time-of-flight mass spectrometry (TOF-MS) data applied to a GaN metalorganic vapor phase epitaxy system. Incorporating ab initio knowledge …

Using Label Information in a Genetic Programming Based Method for Acquiring Tag Tree Patterns with Vertex Labels and Wildcards Open

Shunsuke Yokoyama, Tetsuhiro Miyahara, Yusuke Suzuki, Tomoyuki Uchida, Tetsuji Kuboyama · 2022

Machine learning and data mining from tree structured data are studied intensively. In this paper, as tree structured patterns we use tag tree patterns with vertex and edge labels and wildcards in order to represent label connecting relati…

Exploration of a large-scale reconstructed structure on GaN(0001) surface by Bayesian optimization Open

Akira Kusaba, Yoshihiro Kangawa, Tetsuji Kuboyama, Atsushi Oshiyama · 2022

GaN(0001) surfaces with Ga- and H-adsorbates are fundamental stages for\nepitaxial growth of semiconductor thin films. We explore stable surface\nstructures with nanometer scale by the density-functional calculations combined\nwith Bayesia…

Exploration of a new reconstructed structure on GaN(0001) surface by Bayesian optimization Open

Akira Kusaba, Yoshihiro Kangawa, Tetsuji Kuboyama, Atsushi Oshiyama · 2021

GaN(0001) surfaces with Ga- and H-adsorbates are fundamental stages for epitaxial growth of semiconductor thin films. We explore stable surface structures with nanometer scale by the density-functional calculations combined with Bayesian o…

Analyzing temporal patterns of topic diversity using graph clustering Open

Takako Hashimoto, David Shepard, Tetsuji Kuboyama, Kilho Shin, Ryota Kobayashi , et al. · 2020

During a disaster, social media can be both a source of help and of danger: Social media has a potential to diffuse rumors, and officials involved in disaster mitigation must react quickly to the spread of rumor on social media. In this pa…

Guest Editorial: Special issue on Discovery Science Open

Takuya Kida, Tetsuji Kuboyama, Takeaki Uno, Akihiro Yamamoto · 2020

Sparsity-Promoting Dynamic Mode Decomposition of Plasma Turbulence Open

Akira Kusaba, Tetsuji Kuboyama, S. Inagaki · 2020

A data-driven approach called sparsity-promoting dynamic mode decomposition (SP-DMD) is applied to the plasma turbulence signals obtained with an azimuthal probe array. The spatiotemporal turbulence can be reasonably decomposed into seven …

Twitter Topic Progress Visualization using Micro-clustering Open

Takako Hashimoto, Akira Kusaba, Dave Shepard, Tetsuji Kuboyama, Kilho Shin , et al. · 2020

A Fast Algorithm for Unsupervised Feature Value Selection Open

Kilho Shin, Kenta Okumoto, David Shepard, Tetsuji Kuboyama, Takako Hashimoto , et al. · 2020

Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement Open

Mikio Mizukami, Kouichi Hirata, Tetsuji Kuboyama · 2019

In this paper, first we formulate the problem of a bipartite edge correlation clustering which finds an edge biclique partition with the minimum disagreement from a bipartite graph, by extending the bipartite correlation clustering which f…

Fast Nearest Neighbor Search with Narrow 16-bit Sketch Open

Naoya Higuchi, Yasunobu Imamura, Tetsuji Kuboyama, Kouichi Hirata, Takeshi Shinohara · 2019

Aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns Open

Fumiya Tokuhara, Tetsuhiro Miyahara, Tetsuji Kuboyama, Yusuke Suzuki, Tomoyuki Uchida · 2018

We propose aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns. The proposed fitness functions estimate the fitness of a set of correlated individuals rather tha…

Nearest Neighbor Search using Sketches as Quantized Images of Dimension Reduction Open

Naoya Higuchi, Yasunobu Imamura, Tetsuji Kuboyama, Kouichi Hirata, Takeshi Shinohara · 2018

sCwc/sLcc: Highly Scalable Feature Selection Algorithms Open

Kilho Shin, Tetsuji Kuboyama, Takako Hashimoto, Dave Shepard · 2017

Feature selection is a useful tool for identifying which features, or attributes, of a dataset cause or explain the phenomena that the dataset describes, and improving the efficiency and accuracy of learning algorithms for discovering such…

siEDM: An Efficient String Index and Search Algorithm for Edit Distance with Moves Open

Yoshimasa Takabatake, Kenta Nakashima, Tetsuji Kuboyama, Yasuo Tabei, Hiroshi Sakamoto · 2016

Although several self-indexes for highly repetitive text collections exist, developing an index and search algorithm with editing operations remains a challenge. Edit distance with moves (EDM) is a string-to-string distance measure that in…

siEDM: an efficient string index and search algorithm for edit distance with moves Open

Yoshimasa Takabatake, Kenta Nakashima, Tetsuji Kuboyama, Yasuo Tabei, Hiroshi Sakamoto · 2016

Although several self-indexes for highly repetitive text collections exist, developing an index and search algorithm with editing operations remains a challenge. Edit distance with moves (EDM) is a string-to-string distance measure that in…

Breaking Anonymity of Social Network Accounts by Using Coordinated and Extensible Classifiers Based on Machine Learning Open

Eina Hashimoto, Masatsugu Ichino, Tetsuji Kuboyama, Isao Echizen, Hiroshi Yoshiura · 2016

High Dimensional Similarity Search with Bundled Query Processing on Hilbert R-Tree Open

Yohei Nasu, Naoki Kishikawa, Kei Tashima, S. Kodama, Yasunobu Imamura , et al. · 2015

Hilbert R-tree is an R-tree, which is a B-tree-like multiway balanced tree, such that data objects with high dimensions are sorted along the Hilbert curve. In this paper, we first point out that the compact Hilbert R-tree, which is a Hilbe…

Classifying Nucleotide Sequences and their Positions of Influenza A Viruses through Several Kernels Open

Issei Hamada, Takaharu Shimada, Daiki Nakata, Kouichi Hirata, Tetsuji Kuboyama · 2015

In this paper, we classify nucleotide sequences and their positions of influenza A viruses by using both nucleotide sequence kernels and phylogenetic tree kernels. In the nucleotide sequence kernel, we regard a nucleotide sequence as a vec…

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