研究者詳細 - 平田　耕一

論文 - 平田　耕一

分割表示 >> ／全件表示215 件中 1 - 215 件目

Improved Prediction of Yeast-Like Fungi in Gram Srtained Smears Images 査読有り国際誌

Tsubasa Tanaka, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Fast Approximate Nearest Neighbor Search via Double Filtering of Quantized Projections 査読有り国際誌

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

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Detecting Bacteria in Gram Stained Smears Images by HIC-YOLO and Its Variants 査読有り国際誌

Hiroto Tabakotani, Ukyo Kashino, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Detecting Bacteria in Gram Stained Smears Images by YOLO and SOD-YOLO 査読有り国際誌

Hikaru Kobata, Ukyo Kashino, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Improved Prediction of Geckler Classification in Gram Stained Smears Images for Sputum 査読有り国際誌

Kei Goto, Masaki Kono, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Classifying Rectangle Regions of Bacteria in Gram Stained Smears Images 査読有り国際誌

Hiromu Kuroishi, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Classifying Entire Images of Samples and Bacteria in Gram Stained Smears Images 査読有り国際誌

Tadashi Morikawa, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Predicting Phagocytotic Activity of Leukocytes in Gram Stained Smears Images 査読有り国際誌

Kouya Kagemoto, Ryunosuke Nakajo, Kouichi Hirata

Proc. 18th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025) 2025年07月

Detecting Bacteria from Gram Stained Smears Images by the Family of YOLOs 査読有り国際誌

Ukyo Kashino, Kyosuke Taira, Kouichi Hirata

Proc. 2024 7th International Conference on Digital Medicine and Image Processing (DMIP 2024) 6 - 10 2025年01月

Detecting Phagocytotic Activity of Leukocytes in Gram Stained Smears Images 査読有り国際誌

Ryunosuke Nakajo, Kouichi Hirata

Proc. 2024 7th International Conference on Digital Medicine and Image Processing (DMIP 2024) 17 - 21 2025年01月

Predicting Yeast-Like Fungi from Gram Stained Smears Images 査読有り国際誌

Tsubasa Tanaka, Kouya Kagemoto, Kouichi Hirata

Proc. 2024 7th International Conference on Digital Medicine and Image Processing (DMIP 2024) 84 - 87 2025年01月

微生物検査領域におけるArtificial Intelligence 招待有り査読有り

平田耕一

臨床検査 ( 医学書院 ) 68 ( 12 ) 1460 - 1464 5ページ 2024年12月

Annotation along Arranged Bacteria to Detect Gram Positive Cocci from Gram Stained Smears Images 査読有り国際誌

Ukyo Kashino, Mayu Yoshida, Kouichi Hirata

Proc. 16th International Conference on E-Service and Knowledge Management 101 - 104 2024年07月

Ancestral-Path Descendant-Labels Histogram Distance for Rooted Labeled Trees 査読有り国際誌

Daisuke Abe, Kouichi Hirata

Proc. 16th International Conference on E-Service and Knowledge Management 72 - 77 2024年07月

Activation Functions for Detection of Bacteria from Gram Stained Smears Images by YOLOv8 査読有り国際誌

Kouya Kagemoto, Kouichi Hirata

Proc. 16th International Conference on E-Service and Knowledge Management 62 - 67 2024年07月

Comparison with Detection of Bacteria from Gram Stained Smears Images by Various Object Detectors 査読有り国際誌

Tsubasa Tanaka, Kouichi Hirata

Proc. 16th International Conference on E-Service and Knowledge Management 58 - 61 2024年07月

Data Augmentation for Detection of Bacteria from Gram Stained Smears Images by YOLOv8 査読有り国際誌

Ryunosuke Nakajo, Minori Tsutsui, Kouichi Hirata

Proc. 16th International Conference on E-Service and Knowledge Management 105 - 108 2024年07月

Subcaterpillar Isomorphism: Subtree Isomorphism for Rooted Labeled Caterpillars 査読有り国際誌

Tomoya Miyazaki, Kouichi Hirata

Recent Advances in Computational Optimization, Studies in Computational Intelligence ( Springer ) 1158 110 - 140 2024年03月

Fast Filtering for Similarity Search Using Conjunctive Enumeration of Sketches in Order of Hamming Distance 査読有り国際誌

Naoya Higuchi, Yosunobu Imamura, Vladimir Mic, Takeshi Shinohara, Kouichi Hirata, Tetsuji Kuboyama

Proc. 13th International Conference on Pattern Recognition Applications and Methods (ICPRAM2023) 499 - 510 2024年02月

Sufficient Algorithm for Inclusion of Pattern Caterpillar in Text Tree 査読有り国際誌

Daisuke Abe, Tomoya Miyazaki, Kouichi Hirata

Proc. 15th International Conference on E-Service and Knowledge Management 128 - 131 2023年07月

Predicting Geckler Classification from Gram Stained Smears Images for Sputum: Image Classification versus Object Detection 査読有り国際誌

Hitoshi Sugimoto, Ryotaro Funatsu, Kouichi Hirata

Proc. 15th International Conference on E-Service and Knowledge Management 122 - 127 2023年07月

Detecting Bacteria Causing Infectious Disease from Gram Stained Smears Images 査読有り国際誌

Ukyo Kashino, Syoma Terada, Kouichi Hirata

Proc. 15th International Conference on E-Service and Knowledge Management 13 - 18 2023年07月

Distance-Based Analysis of Positions in Amino Acid Sequences for Structural Proteins of SARS-CoV-2 Delta and Omicron Variants 査読有り国際誌

Ryota Nagashima, Uran Yamamoto, Kouichi Hirata

Proc. 15th International Conference on E-Service and Knowledge Management 39 - 44 2023年07月

イギリスで“science"が科学を意味するようになったのはいつなのか?

園井千音, 平田耕一

大分大学理工学部紀要 ( 大分大学理工学部 ) 1 22 - 30 2023年06月

担当区分：責任著者記述言語：日本語掲載種別：記事・総説・解説・論説等（大学・研究所紀要）

In this paper, we discuss when the word “science" mean science in the current sense in England. Then, by focusing on Journal of Science and the Arts published in 1817 and Edinburgh Journal of Science published in 1824, we point out that the word “science" meant science about 1817 in academic sense and it became the general sense about 1824 for the public.

DOI： 10.51073/17215

Subcaterpillar Isomorphism between Caterpillars: Subtree Isomorphism Restricted Text and Pattern Trees To Caterpillars 査読有り国際誌

Tomoya Miyazaki, Kouichi Hirata

Proc. 12th International Conference on Pattern Recognition Applications and Methods (ICPRAM2023) 89 - 94 2023年02月

Correlated Mutations of Positions among Structural Proteins in Delta and Omicron Variants for SARS-CoV-2 Amino Acid Sequences 査読有り国際誌

Yuishi Shimaya, Kouichi Hirata

Proc. 12th International Conference on Pattern Recognition Applications and Methods (ICPRAM2023) 344 - 349 2023年02月

微生物検査領域における人工知能導入の可能性招待有り査読有り

平田耕一

検査と技術 ( 医学書院 ) 51 ( 1 ) 48 - 50 2023年01月

Subcaterpillar Isomorphism: Subtree Isomorphism Restricted Pattern Trees to Caterpillars 査読有り国際誌

Tomoya Miyazaki, Kouichi Hirata

Proc. 17th Conference on Compute Science and Intelligence Systems (FedCSIS 2022) 351 - 356 2022年09月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Bulgaria Sofia 2022年09月04日 - 2022年09月07日

In this paper, we investigate a subcaterpillar isomorphism that is a problem, for a rooted labeled caterpillar P and a rooted labeled tree T, of determining whether or not there exists a subtree in T which is isomorphic to P. Then, we design two algorithms to solve the subcaterpillar isomorphism for a caterpillar P and a tree T in (i) O(p + tDhσ) time and O(Dh) space and in (ii) O(p + tDσ) time and O(D(h + H)) space, respectively. Here, p is the number of vertices in P, t is the number of vertices in T, h is the height of P, H is the height of T, σ is the number of alphabets for labels and D is the degree of T. Furthermore, we give experimental results of the two algorithms for artificial data and real data.

DOI： 10.15439/2022F113

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85141180597&origin=inward

Segmental Distance between Rooted Labeled Caterpillars 査読有り国際誌

Manami Hagihara, Tomoya Miyazaki, Kouichi Hirata

Proc. 14th International Conference on E-Service and Knowledge Management 107 - 112 2022年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Kanazawa 2022年07月03日 - 2022年07月07日

A segmental distance for rooted labeled unordered trees is the edit distance such that the insertion and the deletion in the edit operations are allowed to either the root or the leaves. In this paper, we design the algorithm of computing the segmental distance for rooted labeled caterpillars in O(n+h2σ) time under the unit cost function, where n is the maximum number of vertices, h is the maximum height and σ is the number of labels, whereas the problem of computing the segmental distance for rooted labeled unordered trees is MAX SNP-hard.

DOI： 10.1109/IIAIAAI55812.2022.00030

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139561095&origin=inward

Object Detection as Gram Positive Cocci in Gram Stained Smear Images 査読有り国際誌

Hitoshi Sugimoto, Kouichi Hirata

Proc. 14th International Conference on E-Service and Knowledge Management 134 - 137 2022年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Kanazawa 2022年07月03日 - 2022年07月07日

In this paper, we detect Gram positive cossi in Gram stained smear images as object detection. As detectors, we adopt Faster R-CNN, RetinaNet and YOLOv5. Then, we give experimental results for detecting Gram positive cocci, and the detection by YOLOv5 is more successful than that by Faster R-CNN and RetinaNet.

DOI： 10.1109/IIAIAAI55812.2022.00035

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139570315&origin=inward

Classifying Gram Positive Cocci and Gram Negative Bacilli in Gram Stained Smear Images 査読有り国際誌

Ibuki Kawano, Eri Kurumida, Syoma Terada, Kouichi Hirata

Proc. 14th International Conference on E-Service and Knowledge Management 55 - 60 2022年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Kanazawa 2022年07月03日 - 2022年07月07日

In this paper, we classify Gram positive cocci and Gram negative bacilli in Gram stained smear images. We adopt pre-trained models of VGG16, VGG19, MobileNet and DenseNet by using ImageNet as learning models. Then, we give experimental results for classifying them, and the classification by MobileNet and DenseNet are more successful than that by VGG16 and VGG19.

DOI： 10.1109/IIAIAAI55812.2022.00021

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139565934&origin=inward

Finding Correlated Mutations of Positions among Structural Proteins in SARS-CoV-2 Amino Acid Sequences 査読有り国際誌

Kan Yonashiro, Yuichi Shimaya, Kouichi Hirata

Proc. 14th International Conference on E-Service and Knowledge Management 61 - 64 2022年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Kanazawa 2022年07月03日 - 2022年07月07日

In this paper, we find the correlated mutations of positions among structural proteins of spike, envelop, membrane and nucleocapsid proteins in amino acid sequences of SARS-CoV-2. Here, we adopt the algorithm designed by Shimada et al. (2012) of finding the correlated mutations formulated by joint entropy. In particular, we focus on whether or not the found correlated mutations contains spike protein substitutions in SARS-CoV-2 Delta variant.

DOI： 10.1109/IIAIAAI55812.2022.00022

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139554865&origin=inward

Caterpillar Inclusion: Inclusion Problem for Rooted Labeled Caterpillars 査読有り国際誌

Tomoya Miyazaki, Manami Hagihara, Kouichi Hirata

Proc. 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM2022) 280 - 287 2022年02月

Computing the Variations of Edit Distance for Rooted Labaled Caterpillars 査読有り国際誌

Manami Hagihara, Takuya Yoshino, Kouichi Hirata

Proc. 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM2022) 272 - 279 2022年02月

Object Detection as Campylobacter Bacteria and Phagocytotic Activity of Leukocytes in Gram Stained Smears Images 査読有り国際誌

Kyohei Yoshihara, Kouichi Hirata

Proc. 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM2022) 1 534 - 541 2022年02月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Online Online 2022年02月03日 - 2022年02月05日

In this paper, we apply object detection to Gram stained smear images, where objects are Campylobacter bacteria and phagocytotic activity of leukocytes. Then, we adopt three CNN-based object detectors of Faster R-CNN, RetinaNet and YOLOv5. The outline of the detection is first to annotate the regions of objects as Campylobacter bacteria and phagocytotic activity of leukocytes in training images, and then to detect the regions of objects in the remained test images by using the detectors. Finally, we give experimental results of detecting Campylobacter bacteria and phagocytotic activity of leukocytes in Gram stained smear images by using the detectors.

DOI： 10.5220/0010813800003122

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139552318&origin=inward

Nearest-Neighbor Search from Large Datasets Using Narrow Sketches 査読有り国際誌

Naoya Higuchi, Yasunobu Imamura, Vladimir Mic, Takeshi Shinohara, Kouichi Hirata, Tetsuji Kuboyama

Proc. 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM2022) 401 - 410 2022年02月

Detecting Camphylobacter Bacteria and Phagocytoic Activity of Leukocytes from Gram Stained Smears Images 査読有り国際誌

Kyohei Yoshihara, Kouichi Hirata

Proc. 12th International Conference on E-Service and Knowledge Management - 10 - 15 2021年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

2021年07月11日 - 2021年07月16日

In this paper, we develop the method to detect Campylobacter bacteria and phagocytotic activity of leukocytes from Gram stained smears images. First, we improve VGG16 by adding batch normalization and by replacing flatten with global average pooling and construct the classifier by using transfer learning model based on the improved VGG16. Then, by comparing the detection by the VGG16 with that by the improved VGG16, for the classification of Camphylobacter bacteria, we give experimental results of classifying Campylobacter images with non-Campylobacter images. On the other hand, for the classification of phagocytotic activity of leukocytes, we give experimental results of classifying phagocytotic images with quasi- and non-phagocytotic images and of classifying phagocytotic images, quasi-phagocytotic images and non-phagocytotic images.

DOI： 10.1109/IIAI-AAI53430.2021.00002

Scopus

CiNii Research

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85133161784&origin=inward

Trim Distance between Positions in Necleotide Sequences for Structural Proteins of SARS-CoV-2 査読有り国際誌

Kan Yonashiro, Kouichi Hirata

Proc. 12th International Conference on E-Service and Knowledge Management - 35 - 40 2021年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

2021年07月11日 - 2021年07月16日

A trim distance between two positions in the set of nucleotide sequences is a tree-based distance between the trimmed phylogenetic trees at two positions, each of which is obtained by applying the label-based closest-neighbor trimming method to the relabeled phylogenetic tree at the position that the index as a label of leaves is relabeled to the nucleotide occurring at the position. In this paper, as a tree-based distance, we adopt a label histogram distance and a depth histogram distance. Then, we introduce new trim distances that a label trim distance and a depth trim distance, respectively. Finally, by using the nucleotide sequences and the reconstructed phylogenetic tree from them provided from NCBI, we investigate the trim distances between the positions in the nucleotide sequences for structural proteins of spike, envelope, membrane and nucleocapsid proteins of SARS-CoV-2.

DOI： 10.1109/IIAI-AAI53430.2021.00006

Scopus

CiNii Research

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85133185828&origin=inward

Leaf-Preserving Distance between Rooted Labeled Caterpillars 査読有り国際誌

Manami Hagihara, Takuya Yoshino, Kouichi Hirata

Proc. 12th International Conference on E-Service and Knowledge Management 23 - 28 2021年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

2021年07月11日 - 2021年07月16日

In this paper, we introduce a leaf-preserving distance between rooted labeled trees (trees, for short) as a distance that a leaf in a tree is corresponding to a leaf in another tree. Then, we show that the leaf-preserving distance is always smaller than or equal to the bottom-up distance and incomparable with the alignment distance, the isolated-subtree distance and the segmental distance, but the problem of computing the leaf-preserving distance between trees is MAX SNP-hard. On the other hand, for a rooted labeled caterpillar (caterpillar, for short) that is a tree transformed to a rooted path after removing all the leaves in it, we design an algorithm to compute the leaf-preserving distance between caterpillars in O(h2λ) time, where h is the maximum height and λ is the maximum number of leaves for given two caterpillars. Finally, we give experimental results for computing the leaf-preserving distance for caterpillars.

DOI： 10.1109/IIAI-AAI53430.2021.00004

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85133160471&origin=inward

Caterpillar Alignment Distace for Rooted Labeled Caterpillars: Distance Based on Alignments Requeired to Be Caterpillars 査読有り

Yoshiyuki Ukita, Takuya Yoshino, Kouichi Hirata

Recent Advances in Computational Optimization 920 111 - 134 2021年01月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

A rooted labeled caterpillar (caterpillars, for short) is a rooted labeled tree transformed to a rooted path after removing all the leaves in it. In this paper, we discuss the alignment distance between two caterpillars, which is formulated as the minimum cost of possible alignments as supertrees of them. First, we point out that, whereas the alignment between two trees is always a tree, the alignment between two caterpillars is not always a caterpillar. Then, we formulate a caterpillar alignment distance such that the alignment is required to be a caterpillar. Also we formulate a caterpillar less-constrained mapping and show that the caterpillar alignment distance coincides with the minimum cost of possible caterpillar less-constrained mappings. Furthermore, we design the algorithm to compute the caterpillar alignment distance between two caterpillars in O(h2λ3) time under the general cost function and in O(h2λ) time under the unit cost function, where h is the maximum height and λ is the maximum number of leaves in caterpillars. Finally, we give experimental results of computing the caterpillar alignment distance.

DOI： 10.1007/978-3-030-58884-7_6

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097616531&origin=inward

グラム染色画像からのキャンピロバクターと白血球貪食の推定

吉原教平, 橋本和貴, 平田耕一

第114回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-C002 7 - 11 2020年11月

Pivot Selection for Narrow Sketches by Optimization Algorithms 査読有り国際誌

Naoya Higuchi, Yasunobu Imamura, Vladimir Mic, Takeshi Shinohara, Kouichi Hirata, Tetsuji Kuboyama

Proc. 13th Interenational Conference on Similarity Search and Application (SISAP2020), Lecture Notes in Computer Science ( Springer-Verlag ) 12440 33 - 46 2020年09月

記述言語：英語掲載種別：研究論文（学術雑誌）

Online Online 2020年09月30日 - 2020年10月02日

Sketches are compact bit strings that are considered as products of an LSH for high-dimensional data. We use them in filtering for narrowing down solution candidates in similarity search. We propose a pivot selection method for narrow sketches with a length such as 16-bits by optimization algorithms with the accuracy of filtering itself as the objective function.

DOI： 10.1007/978-3-030-60936-8_3

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85093832416&origin=inward

狭い16ビットのスケッチを用いた高速最近傍検索査読有り

樋口直哉, 今村安伸, 久保山哲二, 平田耕一, 篠原武

情報処理学科論文誌数理モデル化と応用 ( 情報処理学会 ) 13 ( 1 ) 13 - 22 2020年03月

Detection System of Gram Types for Bacteria from Gram Stained Smears Images 査読有り国際誌

Ryosuke Iida, Kazuki Hashimoto, Kouichi Hirata, Kimiko Matsuoka, Shigeki Yokoyama

Proc. 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM2020) 477 - 484 2020年02月

Heavy Caterpillar Distances for Rooted Labeled Unordered Trees 査読有り国際誌

Nozomi Abe, Takuya Yoshino, Kouichi Hirata

Proc. 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM2020) 198 - 204 2020年02月

Detecting Geckler Classification from Gram Stained Smears Images for Sputum 査読有り国際誌

Kazuki Hashimoto, Ryosuke Iida, Kouichi Hirata, Kimiko Matsuoka, Shigeki Yokoyama

Proc. 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM2020) 469 - 476 2020年02月

Path Histogram Distance and Complete Subtree Histogram Distance for Rooted Labeled Caterpillars 査読有り国際誌

Taiga Kawaguchi, Takuya Yoshino, Kouichi Hirata

Journal of Information and Telecommunication 4 ( 2 ) 199 - 212 2020年01月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

A rooted labelled caterpillar (a caterpillar, for short) is a rooted labelled unordered tree transformed to a path after removing all the leaves in it. In this paper, we discuss two histogram distance between caterpillars. One is a path histogram distance as an L1-distance between the histograms of paths from the root to every leaf and another is a complete subtree histogram distance as an L1-distance between the histograms of complete subtrees for every node. While the latter is always a metric for general trees, the former is not a metric. In this paper, we show that, for caterpillars, the path histogram distance is always a metric, simply linear-time computable and incomparable with the edit distance. Furthermore, we give experimental results for caterpillars in real data of comparing the path histogram distance and the complete subtree histogram distance with the isolated-subtree distance as the most general tractable variation of the edit distance.

DOI： 10.1080/24751839.2020.1718443

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104838825&origin=inward

Annealing by Increasing Resampling 査読有り国際誌

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

Lecture Notes in Computer Science 11996 71 - 92 2020年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Annealing by Increasing Resampling (AIR, for short) is a stochastic hill-climbing optimization algorithm that evaluates the objective function for resamplings with increasing size. At the beginning stages, AIR makes state transitions like a random walk, because it uses small resamplings for which evaluation has large error at high probability. At the ending stages, AIR behaves like a local search because it uses large resamplings very close to the entire sample. Thus AIR works similarly as the conventional Simulated Annealing (SA, for short). As a rationale for AIR approximating SA, we show that both AIR and SA can be regarded as a hill-climbing algorithm according to objective function evaluation with stochastic fluctuations. The fluctuation in AIR is explained by the probit, while in SA by the logit. We show experimentally that the logit can be replaced with the probit in MCMC, which is a basis of SA. We also show experimental comparison of SA and AIR for two optimization problems, sparse pivot selection for dimension reduction, and annealing-based clustering. Strictly speaking, AIR must use resampling independently performed at each transition trial. However, it has been demonstrated by experiments that reuse of resampling within a certain number of times can speed up optimization without losing the quality of optimization. In particular, the larger the samples used for evaluation, the more remarkable the superiority of AIR is in terms of speed with respect to SA.

DOI： 10.1007/978-3-030-40014-9_4

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85079553108&origin=inward

Fast Filtering for Nearest Neighbor Search by Sketch Enumeration without Using Matching 査読有り国際誌

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

Proc. 32nd Australian Joint Conference on Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence 11919 240 - 252 2019年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

オーストラリアアデレード 2019年12月02日 - 2019年12月05日

A sketch is a lossy compression of high-dimensional data into compact bit strings such as locality sensitive hash. In general, k nearest neighbor search using sketch consists of the following two stages. The first stage narrows down the top K candidates, for some K ≥ k,, using a priority measure of sketch as a filter. The second stage selects the k nearest objects from K candidates. In this paper, we discuss the search algorithms using fast filtering by sketch enumeration without using matching. Surprisingly, the search performance is rather improved by the proposed method when narrow sketches with smaller number of bits such as 16-bits than the conventional ones are used. Furthermore, we compare the search efficiency by sketches of various widths for several databases, which have different numbers of objects and dimensionalities. Then, we can observe that wider sketches are appropriate for larger databases, while narrower sketches are appropriate for higher dimension.

DOI： 10.1007/978-3-030-35288-2_20

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076560904&origin=inward

Alignment for Rooted Labeled Caterpillars 査読有り

Yoshiyuki Ukita, Takuya Yoshino, Kouichi Hirata

Preprints of Position Papers of the 2019 Federated Conference on Computer Science and Information Systems 12 - 25 2019年09月

Iterative Consistency-Based Feature Selection and Its Application to Nucleotide Sequences of Influenza A Viruses 査読有り

Sho Shimamura, Kouichi Hirata

Information Engineering Express 5 ( 1 ) 86 - 96 2019年05月

Introducing Fluctuation into Increasing Order of Symmetric Uncertainty for Consistency-Based Feature Selection 査読有り

Sho Shimamura, Kouichi Hirata

Proc. 15th Annual Conference on Theory and Applications of Models of Computation, Lecture Notes in Computer Science 11436 550 - 565 2019年04月

The Reselection of Adjacent Sets by Consistency-Based Feature Selection Algorithm 査読有り

Sho Shimamura, Kouichi Hirata

Proc. 2nd International Conference on Information Science and System 4 pages 2019年03月

グラム染色画像からの菌分類推定システムの開発

橋本和貴, 飯田亮介, 平田耕一

第109回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B803 99 - 104 2019年03月

Annealing by Increasing Resampling in the Unified View of Simulated Annealing 査読有り

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

Proc. 8th International Conference on Pattern Recognition Applications and Methods 173 - 180 2019年02月

Vertical and Horizontal Distances to Approximate Edit Distance for Rooted Labeled Caterpillars 査読有り

Kohei Muraka, Takuya Yoshino, Kouichi Hirata

Proc. 8th International Conference on Pattern Recognition Applications and Methods 590 - 597 2019年02月

Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement 査読有り

Mikio Mizukami, Tetsuji Kuboyama, Kouichi Hirata

Proc. 8th International Conference on Pattern Recognition Applications and Methods 699 - 706 2019年02月

Fast Nearest Neighbor Search with Narrow 16-Bit Sketch 査読有り

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

Proc. 8th International Conference on Pattern Recognition Applications and Methods 540 - 547 2019年02月

Earth Mover's Distance Between Rooted Labeled Unordered Trees Formulated from Complete Subtrees 査読有り

Taiga Kawaguchi, Takuya Yoshino, Kouichi Hirata

ICPRAM2018: Proc. International Conference on Pattern Recognition Applications and Methods, Lecture Notes in Artificial Intelligence 11351 65 - 88 2019年01月

LCA Histogram Distance for Rooted Labeled Caterpillars 査読有り

Takuya Yoshino, Kohei Muraka, Kouichi Hirata

Proc. 10th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2018) 2018年09月

Computing Edit Distance between Rooted Labeled Caterpillars 査読有り国際誌

Kohei Muraka, Takuya Yoshino, Kouichi Hirata

Proc. Federated Conference on Computer Science and Information Systems (FedGCSIS 2018) 245 - 252 2018年09月

根付きラベル付きキャタピラの編集距離の計算

村家康平, 芳野拓也, 平田耕一

第107回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B801 14 - 19 2018年08月

二部辺相関クラスタリングとその乱択アルゴリズム

水上幹朗, 平田耕一

第107回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B801 26 - 31 2018年08月

外平面的グラフの線形時間認識アルゴリズムの実装

浮田誉之, 平田耕一

第107回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B801 20 - 25 2018年08月

Path Histogram Distance for Rooted Labeled Caterpillars 査読有り

Taiga Kawaguchi, Takuya Yoshino, Kouichi Hirata

Proc. 10th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2018), Lecture Notes in Artificial Intelligence 10751 10751 276 - 286 2018年03月

根付きラベル付きキャタピラのパスヒストグラム距離

川口泰雅, 芳野拓也, 平田耕一

第105回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B508 27 - 32 2018年01月

Earth Mover's Distance for Rooted Labeled Unordered Trees based on Tai Mapping Hierarchy 査読有り

Taiga Kawaguchi, Kouichi Hirata

Proc. 7th International Conference on Pattern Recognition Applications and Methods 159 - 168 2018年01月

Nearest Neighbor Search using Sketches as Quantized Images of Dimension Reduction 査読有り

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

Proc. 7th International Conference on Pattern Recognition Applications and Methods 356 - 363 2018年01月

Extacting Mutually Dependent Multisets 査読有り

Natsuki Kiyota, Sho Shimamura, Kouichi Hirata

Proc. 20th International Conference on Discovery Science (DS 2017), Lecture Notes in Artificial Intelligence 10558 267 - 280 2017年10月

Pivot Selection for Dimension Reduction using Annealing by Increasing Resampling 査読有り

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

Proc. Learn. Wissen. Daten, Analysen. (LWDA 2017) 15 - 24 2017年09月

On the Earth Mover's Distances Based on Complete Subtrees for Rooted Labeled Trees 査読有り

Taiga Kawaguchi, Kouichi Hirata

Proc. 2017 International Workshop on Smart Info-Media Systems in Asia (SISA 2017) 225 - 228 2017年09月

On the Applications of Iterative Consistency-Based Feature Selection to Nucleotide Sequences for Influenza A Viruses 査読有り

Sho Shimamura, Kouichi Hirata

Proc. 2017 International Workshop on Smart Info-Media Systems in Asia (SISA 2017) 234 - 237 2017年09月

Anchored Alignment Distance between Rooted Labeled Unordered Trees 査読有り

Takuya Yoshino, Yuma Ishizaka, Kouichi Hirata

Proc. Federated Conference on Computer Science and Information Systems (FedGCSIS 2017) 439 - 446 2017年09月

Taiマッピング階層に基づく根付きラベル付き無順序木の地均し距離

川口泰雅, 平田耕一

第104回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B507 2017年08月

Iterative Feature Selection Based on Binary Consistency 査読有り

Sho Shimamura, Kouichi Hirata

Proc. 8th International Conference on E-Service and Knowledge Management (ESKM 2017) 396 - 399 2017年07月

Tai Mapping Hierarchy for Rooted Labeled Trees through Common Subforest 査読有り

Takuya Yoshino, Kouichi Hirata

Theory of Computing Systems 60 ( 4 ) 759 - 783 2017年05月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

A Tai mapping between two rooted labeled trees (trees, for short) is a one-to-one node correspondence preserving ancestors and siblings (if trees are ordered). The variations of the Tai mapping are known to provide a hierarchy, called a Tai mapping hierarchy. In this paper, we characterize the Tai mapping hierarchy as a common subforest by focusing on the connections of nodes and the arrangements of subtrees in a common subforest. Then, we fill a gap in the Tai mapping hierarchy by introducing several new variations. Furthermore, we summarize and investigate the time complexity of computing the variations of the edit distance as the minimum cost of the variations of the Tai mapping.

DOI： 10.1007/s00224-016-9705-1

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84984870470&origin=inward

多項式時間計算可能な根無しラベル付き木の編集距離

芳野拓也, 平田耕一

第103回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B506 73 - 77 2017年03月

アンチバイオグラムからの相互依存重集合の抽出

清田菜月, 平田耕一

第103回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B506 95 - 100 2017年03月

根付きラベル付き木の地均し距離について

川口泰雅, 平田耕一

第103回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B506 84 - 88 2017年03月

『種の起源』出版後の19世紀イギリス及びアメリカ社会における進化思想の流布について

園井千音, 平田耕一

大分大学工学部研究報告 ( 64 ) 2017年02月

反復特徴選択を用いた塩基配列の解析

嶋村翔, 平田耕一

第102回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B505 1 - 4 2016年12月

Fast Hilbert Sort Algorithm without Using Hilbert Indices 査読有り

Yasunobu Imamura, Takeshi Shinohara, Kouichi Hirata, Tetsuji Kuboyama

Proc. 9th International Conference on Similarity Search and Applications (SISAP 2016), Lecture Notes in Artificial Intelligence 9939 259 - 267 2016年10月

On Temporal and Regional Analysis for Nucleotide Sequences of Influenza A (H1N1) Viruses Based on Feature Selection 査読有り

Sho Shimamura, Kouichi Hirata

Proc. 2016 International Workshop on Smart Info-Media Systems in Asia (SISA 2016) 38 - 42 2016年09月

Enhanced Tai Mapping for Unrooted Trees 査読有り

Takuya Yoshino, Kouichi Hirata

Proc. 2016 International Workshop on Smart Info-Media Systems in Asia (SISA 2016) 6 - 12 2016年09月

特徴選択に基づくA型H1N1亜型インフルエンザウイルス塩基配列の時間性および地域性の解析

嶋村翔, 平田耕一

第101回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B504 68 - 72 2016年08月

根付きラベル付き無順序木のアンカーアライメント距離

芳野拓也, 石坂悠眞, 平田耕一

第101回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B504 1 - 6 2016年08月

Extracting Propagation Patterns from Bacterial Culture Data in Medical Facility 査読有り

Kazuki Nagayama, Kouichi Hirata, Shigeki Yokoyama, Kimiko Matsuoka

New Frontiers in Artificial Intelligence, Lecture Notes in Artificial Intelligence 10091 409 - 417 2016年07月

Taiマッピングの根無し木への拡張

芳野拓也, 平田耕一

第99回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B502 55 - 60 2016年01月

根付き木のアンカーアライメントの実装

石坂悠眞, 芳野拓也, 平田耕一

第99回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B502 39 - 44 2016年01月

根付きラベル付き木のTaiマッピングと共通部分森の関係

芳野拓也, 平田耕一

第98回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B501 1 - 6 2015年08月

A型インフルエンザウイルスのRNA分節における極大対合ヘアピンループ探索

嶋村翔, 平田耕一

第98回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B501 36 - 41 2015年08月

Mapping Kernels Between Rooted Labeled Trees Beyond Ordered Trees 査読有り

Kouichi Hirata, Tetsuji Kuboyama, Takuya Yoshino

New Frontiers in Artificial Intelligence, Lecture Notes in Artificial Intelligence 9067 317 - 330 2015年04月

Central Point Selection for Dimension Reduction Projection Simple-Map Using Binary Quantization 査読有り

Quming Jin, Masaya Nakashima, Takeshi Shinohara, Kouichi Hirata, Tetsuji Kuboyama

New Frontiers in Artificial Intelligence, Lecture Notes in Artificial Intelligence 9067 310 - 316 2015年04月

Anchored Alignment Problem for Rooted Labeled Trees 査読有り

Yuma Ishizaka, Takuya Yoshino, Kouichi Hirata

New Frontiers in Artificial Intelligence, Lecture Notes in Artificial Intelligence 9067 296 - 309 2015年04月

根付き木のアンカーアライメント問題

石坂悠眞, 芳野拓也, 平田耕一

第95回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B402 14 - 19 2014年10月

巡回的順序木のアライメント

芳野拓也, 平田耕一

第94回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B401 29 - 34 2014年07月

Tractable and Intractable Variations of Unordered Tree Edit Distance 査読有り国際誌

Yoshiyuki Yamamoto, Kouichi Hirata, Tetsuji Kuboyama

International Journal of Foundations of Computer Science 25 ( 3 ) 307 - 330 2014年07月

Segmental Mapping and Distance between Rooted Labeled Ordered Trees 査読有り

Tomohiro Kan, Shoichi Higuchi, Kouichi Hirata

Fundamenta Informaticae 132 1 - 23 2014年04月

Agreement Subtree Mapping Kernel for Phylogenetic Trees 査読有り

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

New Frontier in Artificial Intellligence, JSAI-isAI 2013 Workshops, Lecture Notes in Artificial Intelligence 8417 321 - 336 2014年04月

Polynomial Delay and Space Discovery of Connected and Acyclic Sub-Hypergraphs in a Hypergraph 査読有り

Kunihiro Wasa, Takeaki Uno, Kouichi Hirata, Hiroki Arimura

Proc. 16th International Conference on Discovery Science (DS2013), Lecture Notes in Artificial Intelligence 8140 308 - 323 2013年10月

Faster Algorithm for Tree Similarity Based on Compressed Enumeration of Bounded-Sized Ordered Subtrees 査読有り

Kunihiro Wasa, Kouichi Hirata, Takeaki Uno, Hiroki Arimura

Proc. 6th International Conference on Similarity Search and Applications (SISAP2013), Lecture Notes in Artificial Intelligence 8199 73 - 84 2013年10月

根付きラベル付き木の断片マッピングの階層

平田耕一

第90回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B301 19 - 24 2013年07月

バズマーケッティングサイトからのコミュニティマッピングの抽出

樋口鐘一, 橋本隆子, 久保山哲二, 平田耕一

第88回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B203 133 - 138 2013年01月

超グラフに含まれる非巡回部分超グラフの効率よい列挙

和佐州洋, 有村博紀, 宇野毅明, 平田耕一

第88回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B203 85 - 90 2013年01月

劣制限マッピングの新たな特徴付けとアライメント距離に関するマッピングの階層

平田耕一

第88回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-B203 51 - 56 2013年01月

An Isolated-Subtree Inclusion for Unordered Trees 査読有り

Takahiro Hokazono, Tomohiro Kan, Yoshiyuki Yamamoto,Kouichi Hirata

Proc. 3rd IIAI International Conference on e-Services and Knowledge Management 2012年09月

Translating XML Documents through Dyck-Typed Regular Translation Elementary Formal Systems 査読有り

Noriko Sugimoto,Kouichi Hirata

Proc. 3rd IIAI International Conference on e-Services and Knowledge Management 2012年09月

On Computing Tractable Variations of Unordered Tree Edit Distance with Network Algorithms 査読有り

Yoshiyuki Yamamoto, Kouichi Hirata, Tetsuji Kuboyama

New Frontiers in Artificial Intelligence: Joint JSAI-isAI 2011 Workshops 215 - 223 2012年07月

An A* Algorithm for Computing Edit Distance between Rooted Labeled Unordered Trees 査読有り

Shoichi Higuchi, Tomohiro Kan, Yoshiyuki Yamamoto, Kouichi Hirata

New Frontiers in Artificial Intelligence: Joint JSAI-isAI 2011 Workshops 186 - 196 2012年07月

On Computing Tractable Variations of Unordered Tree Edit Distance with Network Algorithms 査読有り

Yoshiyuki Yamamoto, Kouichi Hirata, Tetsuji Kuboyama

Pre-Proc. Second Workshop on Algorithms for Large-Scale Information Processing in Knowledge Discovery (ALSIP 2011) 6 2011年12月

An A* Algorithm for Computing Edit Distance between Rooted Labeled Unordered Trees 査読有り

Shoichi Higuchi, Tomohiro Kan, Yoshiyuki Yamamoto, Kouichi Hirata

Pre-Proc. Second Workshop on Algorithms for Large-Scale Information Processing in Knowledge Discovery (ALSIP 2011) 6 2011年12月

Improved MAX SNP-Hard Results for Finding an Edit Distances between Unordered Trees 査読有り

Kouichi Hirata,Yoshiyuki Yamamoto,Tetsuji Kuboyama

Proc. 22nd Annual Symposium on Combinatorial Pattern Matching (CPM2011) 2011年06月

A Bottom-Up Edit Distance between Rooted Labeled Trees 査読有り

Yoshiyuki Yamamoto,Kouichi Hirata,Tetsuji Kuboyama

Proc. 7th Workshop on Learning with Logics and Logics for Learning 26 - 33 2011年03月

Broom Distance between Rooted Labeled Trees 査読有り

Tetsuji Kuboyama,Kouichi Hirata

Proc. 7th Workshop on Learning with Logics and Logics for Learning 34 - 41 2011年03月

On Learning Dyck-Typed Regular Translation Elementary Formal Systems with Tag Operations between XML Documents 査読有り

Noriko Sugimoto,Kouichi Hirata

Proc. 7th Workshop on Learning with Logics and Logics for Learning 4 - 10 2011年03月

Discovering Global Propagation for Influenza A Viruses Based on Robinson-Foulds Distance between Phylogenetic Trees 査読有り

Kazuya Sata,Kouichi Hirata,Kimihito Ito,Tetsuji Kuboyama

Annual International Conference on BioInformatics and Computational Biology (BICB 2011) 2011年03月

Predicting Mutation Trend of Influenza A Virus through Dimensionality Reduction in Hamming Metric on HA Amino Acid Sequences 査読有り

Tetsuji Kuboyama,Kimihito Ito,Kouichi Hirata,Hiroshi Sakamoto

Annual International Conference on BioInformatics and Computational Biology (BICB 2011) 2011年03月

Aligned Bipartite Episodes between the Genera of Bacteria 査読有り

Takashi Katoh,Kouichi Hirata,Hiroki Arimura,Shigeki Yokoyama,Kimiko Matsuoka

Proc. 2010 IEEE/ICME International Conference on Complex Medical Engineering (CME2010) 193 - 197 2010年07月

Temporal Interrelations of Bacteria Based on the Occurrence Time 査読有り

Kouichi Hirata,Kenishiro Motoyama,Shigeki Yokoyama,Kimiko Matsuoka

Proc. 2010 IEEE/ICME International Conference on Complex Medical Engineering (CME2010) 188 - 192 2010年07月

Approximating Tree Edit Distance through String Edit Distance for Binary Tree Codes 査読有り

Taku Aratsu,Kouichi Hirata,Tetsuji Kuboyama

Fundamenta Informaticae 101 ( 1 ) 1 - 15 2010年04月

An Efficient Depth-First Search Algorithm for Extracting Frequent Diamond Episodes from Event Sequences 査読有り

Takashi Katoh,Hiroki Arimura,Kouichi Hirata

情報処理学会論文誌：データベース(TOD) 2 ( 4 ) 1 - 12 2009年12月

Mining Frequent Bipartite Episode from Event Sequences 査読有り

Takashi Katoh,Hiroki Arimura,Kouichi Hirata

Proc. 12th International Conference on Discovery ScienceLecture Notes in Artificial Intelligence 5808 136 - 151 2009年10月

Discovering Networks for Global Propagation of Influenza A (H3N2) Viruses by Clustering 査読有り

Kazuya Sata,Kouichi Hirata,Kimihito Ito,Tetsuji Kuboyama

Proc. 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES 2009)Lecture Notes in Artificial Intelligence 5712 490 - 497 2009年09月

Mining Frequent k-Partite Episodes from Event Sequences 査読有り

Takashi Katoh,Hiroki Arimura,Kouichi Hirata

Proc. 6th Workshop on Learning with Logics and Logics for Learning 43 - 50 2009年07月

Mining Frequent k-Partite Episodes from Event Sequences 査読有り

Takashi Katoh,Hiroki Arimura,Kouichi Hirata

New Frontiers in Artificial Intelligence: Joint JSAI-isAI 2009 Workshops,Lecture Notes in Artificial Intelligence 6284 331 - 344 2009年07月

Local Frequency Distances for Rooted Ordered Trees 査読有り

Taku Aratsu,Kouichi Hirata,Tetsuji Kuboyama

Proc. 6th Workshop on Learning with Logics and Logics for Learning 11 - 18 2009年07月

A Polynomial-Delay Polynomial-Space Algorithm for Extracting Frequent Diamond Episodes from Event Sequences 査読有り

Takashi Katoh,Hiroki Arimura,Kouichi Hirata

Proc. 13th Pacific-Asia Conference on Knowledge Discovery and Data MiningLecture Notes in Artificial Intelligence 5476 172 - 183 2009年04月

Extracting Sequential Episodes Representing Replacements of Bacteria from Bacterial Culture Data 査読有り

Takashi Katoh,Kouichi Hirata,Hiroki Arimura,Shigeki Yokoyama,Kimiko Matsuoka

Proc. 2009 IEEE/ICME International Conference on Complex Medical Engineering (CME2009) 2009年04月

Approximating Tree Edit Distance through String Edit Distance for Binary Tree Code 査読有り

Taku Aratsu,Kouichi Hirata,Tetsuji Kuboyama

Proc. 35th International Conference on Current Trends in Theory and Practice of Computer Science,Lecture Notes in Computer Science 5404 93 - 104 2009年01月

On Generating Maximal Acyclic Subhypergraphs with Polynomial Delay 査読有り

Taishin Daigo,Kouichi Hirata

Proc. 35th International Conference on Current Trends in Theory and Practice of Computer Science,Lecture Notes in Computer Science 5404 181 - 192 2009年01月

二分木符号の文字列編集距離による木の編集距離の近似

荒津拓,平田耕一,久保山哲二

第71回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A802 57 - 62 2008年09月

極大非巡回部分超グラフの多項式遅延列挙アルゴリズム

大梧諦真,平田耕一

第70回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A801 1 - 8 2008年07月

An Efficient Unordered Tree Kernel and Its Application to Glycan Classification 査読有り

Tetsuji Kuboyama,Kouichi Hirata,Kiyoko F. Kinoshita

Proc. 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2008), Lecture Notes in Artificial Intelligence 5012 184 - 195 2008年05月

A Simple Characterization on Serially Constructible Episodes 査読有り

Takashi Katoh,Kouichi Hirata

Proc. 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2008), Lecture Notes in Artificial Intelligence 5012 600 - 607 2008年05月

A Tree Distance Function Based on Multi-sets 査読有り

Arnoldo Jose Muller Molina,Kouichi Hirata,Takeshi Shinohara

Proc. ALSIP'08, Working Notes of PAKDD Workshops 90 - 100 2008年05月

A Tree Distance Function Based on Multi-sets 査読有り

Arnoldo Jose Muller Molina,Kouichi Hirata,Takeshi Shinohara

JSAI PAKDD 2008 Post-Workshop ProceedingsLecture Notes in Artificial Intelligence 5433 87 - 98 2008年05月

Sibling Distance for Rooted Labeled Trees 査読有り

Taku Aratsu,Kouichi Hirata,Tetsuji Kuboyama

JSAI PAKDD 2008 Post-Workshop ProceedingsLecture Notes in Artificial Intelligence 5433 99 - 110 2008年05月

Sibling Distance for Rooted Labeled Trees 査読有り

Taku Aratsu,Kouichi Hirata,Tetsuji Kuboyama

Proc. ALSIP'08, Working Notes of PAKDD Workshops 101 - 112 2008年05月

極大非巡回部分超グラフの列挙アルゴリズム

大梧諦真,平田耕一

第68回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A703 49 - 52 2008年01月

単純で高速な根付きラベル付き木の類似度

荒津拓,平田耕一

第68回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A703 53 - 58 2008年01月

Mining Frequent Diamond Episodes from Event Sequences 査読有り

Takashi Katoh,Kouichi Hirata,Masateru Harao

Proc. 4th International Conference on Modeling Decisions for Artificial Intelligence (MDAI2007), Lecture Notes in Artificial Intelligence 4617 477 - 488 2007年08月

Inspection of the Effect of Route Information in Traffic Control by Multiagent Simulation 査読有り

Ken Harada,Masateru Harao,Kouichi Hirata

CD-ROM Proc. 4th International Conference on Modeling Decisions for Artificial Intelligence (MDAI2007) 60 - 67 2007年08月

直列エピソードから構成可能なエピソードのグラフ理論的性質

河東孝,平田耕一

第66回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A701 47 - 52 2007年07月

帰納的実数値関数の帰納的枚挙可能集合の学習可能性

廣渡栄寿,平田耕一,宮原哲浩

第66回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A701 7 - 12 2007年07月

Learnability of Recursively Enumerable Sets of Recursive Real-Valued Functions 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara

Proc. CiE2007(Computability in Europe), University of Siena, Technical Report 487 186 - 193 2007年06月

Mining Frequent Elliptic Episodes from Event Sequences 査読有り

Takashi Katoh,Kouichi Hirata

Proc. 5th Workshop on Learning with Logics and Logics for Learning (LLLL2007) 46 - 52 2007年06月

A Minimal Acyclic Generalization with Tractable Removal of Redundancy 査読有り

Megumi Kuwabara,Kouichi Hirata,Masateru Harao

Proc. 5th Workshop on Learning with Logics and Logics for Learning (LLLL2007) 25 - 31 2007年06月

Extraction of Sectorial Episodes Representing Changes for Drug Resistance and Replacements of Bacteria 査読有り

Takashi Katoh,Kouichi Hirata,Masateru Harao,Shigeki Yokoyama,Kimiko Matsuoka

Proc. IEEE/ICME International Conference on Complex Medical Engineering (CME2007) 304 - 309 2007年05月

Efficient Schema Matching Algorithm Based on Pre-checking 査読有り

Kengo Kubo,Keizo Yamada,Kouichi Hirata,Masateru Harao

Systems and Computers in Japan 38 ( 4 ) 143 - 151 2007年04月

A Spectrum Tree Kernel 査読有り

Tetsuji Kuboyama,Kouichi Hirata,Hisashi Kashima,Kiyoko F. Aoki-Kinoshita,Hiroshi Yasuda

Journal of JSAI 22 ( 2 ) 140 - 147 2007年01月

A Gram Distribution Kernel Applied to Glycan Classification and Motif Extraction 査読有り

Tetsuji Kuboyama,Kouichi Hirata,Kiyoko F. Aoki-Kinoshita,Hisashi Kashima,Hiroshi Yasuda

Proc. 17th International Conference on Genome Informatics (GIW2006) 25 - 34 2006年12月

Mining Sectorial Episodes from Event Sequences 査読有り

Takashi Katoh,Kouichi Hirata,Masateru Harao

Proc. 9th International Conference on Discovery Science (DS2006), Lecture Notes in Artificial Intelligence 4265 137 - 148 2006年10月

根付き無順序木のフィルタリング

大倉暢仁,平田耕一,久保山哲二,原尾政輝

第63回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A601 19 - 24 2006年09月

イベント列からの扇状エピソード抽出

河東孝,平田耕一,原尾政輝

第63回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A601 39 - 44 2006年09月

幅限定節の最小汎化

桑原恵,平田耕一,原尾政輝

第63回人工知能学会基本問題研究会, 人工知能学会研究会資料 SIG-FPAI-A601 89 - 94 2006年09月

Finite Prediction of Recursive Real-Valued Functions 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara

Proc. Computability in Europe 2006 (University of Wales Swansea, Computer Science Report Series, Report # CSR 7-2006) 140 - 149 2006年07月

The Gram Distribution for Rooted Ordered Trees 査読有り

Nobuhito Ohkura,Kouichi Hirata,Tetsuji Kuboyama,Masateru Harao,Shin-Ichi Nakano

Proc. 4th Workshop on Learning with Logics and Logics for Learning (LLLL2006) 69 - 77 2006年06月

Extraction of Frequent Causal Episodes from Bacterial Culture Data 査読有り

Takashi Katoh,Kouichi Hirata,Masateru Harao

Proc. 4th Workshop on Learning with Logics and Logics for Learning (LLLL2006) 53 - 60 2006年06月

Subsumption Algorithm for Chordal Clauses 査読有り

Megumi Kuwabara,Kouichi Hirata,Masateru Harao

Proc. 4th Workshop on Learning with Logics and Logics for Learning (LLLL2006) 23 - 30 2006年06月

A q-Grams Based Distance Measure for Ordered Labeled Trees 査読有り

Tetsuji Kuboyama,Kouichi Hirata,Nobuhito Ohkura,Masateru Harao

Proc. 4th Workshop on Learning with Logics and Logics for Learning (LLLL2006) 77 - 83 2006年06月

Prediction-Hardness of Acyclic Conjunctive Queries 査読有り

平田　耕一

Theoretical Computer Science 348 ( 1 ) 84 - 94 2005年12月

帰納的実数値関数の有限予測と無矛盾推論

廣渡栄寿,平田耕一,宮原哲浩

第61回人工知能学会基本問題研究会人工知能学会研究会資料 SIG-FPAI-A503 81 - 86 2005年11月

Chordal Clause の包摂アルゴリズムについて

桑原恵,平田耕一,原尾政輝

第61回人工知能学会基本問題研究会人工知能学会研究会資料 SIG-FPAI-A503 63 - 68 2005年11月

根付き順序木のグラム分散

大倉暢仁,平田耕一,久保山哲二,中野眞一

第61回人工知能学会基本問題研究会人工知能学会研究会資料 SIG-FPAI-A503 51 - 56 2005年11月

The q-Gram Distance for Ordered Unlabeled Trees 査読有り

Nobuhito Ohkura,Kouichi Hirata,Tetsuji Kuboyama,Masateru Harao

Proc. 8th International Conference on Discovery Science (DS2005), Lecture Notes in Artificial Intelligence 3735 189 - 202 2005年10月

ラベル無し順序木のqグラム距離

大倉暢仁,平田耕一,久保山哲二,原尾政輝

コンピュテーション研究会, 信学技法 COMP2005-31 105 25 - 29 2005年09月

On Finding Acyclic Subhypergrahs 査読有り

Megumi Kuwabara,Kouichi Hirata,Masateru Harao

Proc. 15th International Symposium on Fundamentals of Computation Theory (FCT2005), Lecture Notes in Computer Science 3623 491 - 503 2005年08月

Performance Support System for Beginners 査読有り

Shogo Ozaki,Masateru Harao,Kouichi Hirata

Proc. 3rd International Conference on Information Technology and Applications (ICITA'2005) 2 415 - 418 2005年07月

Multi-Agent Based Modeling and Simulation of Consensus Formations in Arguments 査読有り

Kosuke Ono,Masateru Harao,Kouichi Hirata

Proc. 3rd International Conference on Information Technology and Applications (ICITA'2005) 1 264 - 267 2005年07月

スキーマ誘導方式を用いたシークェント形式汎用定理自動証明器の開発

尹淑萍,山田敬三,原尾政輝,平田耕一

夏のLAシンポジウム2005 2005年07月

Prediction of Real-Valued Functions from Finite Examples 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara

New Frontiers in Artificial Intelligence (Joint JSAI 2005 Workshop Post-Proceedings), Lecture Notes in Artificial Intelligence 4012 224 - 234 2005年06月

On Generalization and Subsumption for Ordered Clauses 査読有り

Megumi Kuwabara,Takeshi Ogawa,Kouichi Hirata,Masateru Harao

New Frontiers in Artificial Intelligence (Joint JSAI 2005 Workshop Post-Proceedings) Lecture Notes in Artificial Intelligence 4012 212 - 223 2005年06月

Prediction of Real-Valued Functions from Finite Examples 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara

Proc. Workshop on Learning with Logics and Logics for Learning (LLLL) 81 - 88 2005年06月

Analogy Based Generic Automatic Theorem Prover 査読有り

Keizo Yamada,Shuping Yin,Masateru Harao,Kouichi Hirata

Proc. Workshop on Learning with Logics and Logics for Learning (LLLL) 28 - 33 2005年06月

Frequent Few-Overlapped Monotone DNF Formulas 査読有り

Yoshikazu Shima,Kouichi Hirata,Masateru Harao

Proc. Workshop on Learning with Logics and Logics for Learning (LLLL) 9 - 15 2005年06月

On Generalization and Subsumption for Ordered Clauses 査読有り

Megumi Kuwabara,Takeshi Ogawa,Kouichi Hirata,Masateru Harao

Proc. Workshop on Learning with Logics and Logics for Learning (LLLL) 21 - 27 2005年06月

Development of a Multi-Agent Based Generic Traffic Simulator 査読有り

Kosuke Ono,Takashi Hata,Toyofumi Maetani,Masateru Harao,Kouichi Hirata

Proc. Agent Network Dynamics and Intelligence (ANDI) 83 - 89 2005年06月

Development of a Multi-Agent Based Generic Traffic Simulator 査読有り

Kosuke Ono,Takashi Hata,Toyofumi Maetani,Masateru Harao,Kouichi Hirata

New Frontiers in Artificial Intelligence (Joint JSAI 2005 Workshop Post-Proceedings) Lecture Note in Artificial Intelligence 4012 249 - 260 2005年06月

On the Prediction of Recursive Real-Valued Functions 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara,Setsuo Arikawa

The First CiE (Computability in Europe) Conference (CiE2005), ILLC Publication 93 - 103 2005年06月

Extraction of Frequent Few-Overlapped Monotone DNF Formulas with Depth-First Prunning 査読有り

Yoshikazu Shima,Kouichi Hirata,Masateru Harao

Proceedings of the 9th Pacific-Aisa Conference on Knowledge Discovery and Data Mining (PAKDD2005), Lecture Notes in Artificial Intelligence 3518 50 - 60 2005年05月

Disjunctive Rules Extracted from MRSA Data with Verification 査読有り

Kouichi Hirata,Yoshikazu Shima,Masateru Harao,Shigeki Yokoyama,Kimiko Matsuoka,Taeko Izumi

Proc. 1st International Conference on Complex Medical Engineering (CME2005) 326 - 330 2005年05月

Risk Management System for Hospital-Acquired Infection Based on Bacterial Culture Database 査読有り

Yuichi Ikenaga,Kouichi Hirata,Masateru Harao,Shigeki Yokoyama,Kimiko Matusoka

Proc. 1st International Conference on Complex Medical Engineering (CME2005) 423 - 427 2005年05月

Attribute Selection Measures with Possibility and Their Application to Classifying MRSA from MSSA 査読有り

Kouichi Hirata,Masateru Harao,Minoru Wada,Shigeki Yokoyama,Kimiko Matusoka

Proc. 1st International Conference on Complex Medical Engineering (CME2005) 418 - 422 2005年05月

Extracting Disjunctive Closed Rules from MRSA Data 査読有り

Yoshikazu Shima,Kouichi Hirata,Masateru Harao,Shigeki Yokoyama,Kimiko Matsuoka,Taeko Izumi

Proc. 1st International Conference on Complex Medical Engineering (CME2005) 315 - 321 2005年05月

Efficiently Computable Classes of Second Order Predicate Schema Matching Problems 査読有り

Masateru Harao,Shuping Yin,Keizo Yamada,Kouichi Hirata

Proc. 19th International Workshop on Unification (UNIF 05) 121 - 134 2005年04月

Efficient Second-Order Predicate Schema Matching Based on Projection Position Indexing 査読有り

Masateru Harao,Shuping Yin,Keizo Yamada,Kouichi Hirata

Proc. 5th International Workshop on the Implementation of Logics (IWIL2004) 31 - 42 2005年03月

Development of an Analogy-Based Generic Sequent Style Automatic Theorem Prover Amalgamated with Intractive Proving 査読有り

Keizo Yamada,Shuping Yin,Masateru Harao,Kouichi Hirat

Proc. 5th International Workshop on the Implementation of Logics (IWIL2004) 78 - 86 2005年03月

Refutability and Reliability for Inductive Inference of Recursive Real-Valued Functions 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara,Setsuo Arikawa

IPSJ Transactions on Mathematical Modeling and Its Application 46 ( SIG2(TOM11) ) 1 - 11 2005年01月

Extracting Minimal and Closed Monotone DNF Formulas 査読有り

Yoshikazu Shima,Shinji Mitsuishi,Kouichi Hirata,Masateru Harao

Proceedings of the 7th International Conference on Discovery Science, Lecture Notes in Artificial Intelligence 3245 298 - 305 2004年10月

Generalization Algorithms for Second-Order Terms 査読有り

Kouichi Hirata,Takeshi Ogawa,Masateru Harao

Proceedings of the 14th International Conference on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 3194 147 - 163 2004年09月

Tractable and Intractable Second-Order Matching Problems 査読有り

Kouichi Hirata,Keizo Yamada,Masateru Harao

Journal of Symbolic Computation 37 ( 5 ) 611 - 628 2004年05月

Extraction of Coverings as Monotone DNF Formulas 査読有り

Kouichi Hirata,Ryosuke Nagazumi,Masateru Harao

Proceedings of the 6th International Conference on Discovery Science (Lecture Notes in Artificial Intelligence 2843) 165 - 178 2003年10月

On Condensation of a Clause 査読有り

平田　耕一

Proceedings of the 13th International Conference on Inductive Logic Programming (Lecture Notes in Artificial Intelligence 2845) 164 - 179 2003年10月

Learning Elementary Formal Systems with Queries 査読有り

Hiroshi Sakamoto,Kouichi Hirata,Hiroki Arimura

Theoretical Computer Science 298 ( 1 ) 21 - 50 2003年04月

Criteria for Inductive Inference with Mind Changes and Anomalies of Recursive Real-Valued Functions 査読有り

Eiju Hirowatari,Kouichi Hirata,Tetsuhiro Miyahara,Setsuo Arikawa

The Transactions of IEICE E86-D ( 2 ) 219 - 227 2003年02月

Pre-Checkingに基づく効率的スキーママッチングアルゴリズム査読有り

久保憲吾,山田敬三,平田耕一,原尾政輝

電子情報通信学会論文誌 J85-D-I ( 2 ) 143 - 151 2002年02月

Prediction-Preserving Reducibility with Membership Queries on Formal Languages 査読有り

Kouichi HIRATA,Hiroshi SAKAMOTO (Kyushu Univ.)

Proceedings of the 13th International Symposium on Fundamentals of Computation Theory (Lecture Notes in Computer Science 2138) 172 - 183 2001年08月

Second-Order Schema Matching Based on Projection Point Labeling 査読有り

Keizo YAMADA,Koichi HIRATA,Masateru HARAO

Proceedings of the 15th International Workshop on Unification 49 - 53 2001年06月

On the Hardness of Learning Acyclic Conjunctive Queries 査読有り

平田　耕一

Proceedings of the 11th International Conference on Algorithmic Learning Theory (Lecture Notes in Artificial Intelligence 1968) 238 - 251 2000年12月

A Constructive Learning of Context-Free Languages with a Subpansive Tree 査読有り

Noriko Sugimoto,Takashi Toyoshima,Shinichi Shimozono,Kouichi Hirata

Proc. 5th International Colloquium on Grammatical Inference (Lecture Notes in Artificial Intelligence 1891) 270 - 283 2000年09月

Flattening and Implication 査読有り

平田　耕一

Proceedings of the 10th International Conference on Algorithmic Learning Theory (Lecture Notes in Artificial Intelligence 1720) 157 - 168 1999年12月

Tractable and Intractable Second-Order Matching Problems 査読有り

Kouichi Hirata,Keizo Yamada,Masateru Harao

Proceedings of the 5th Annual International Computing and Combinatorics Conference (Lecture Notes in Computer Science 1627) 432 - 441 1999年07月

Efficient Second-Order Predicate Schema Matching Algorithm 査読有り

Masateru Harao,Keizo Yamada,Kouichi Hirata

Proc. Korea-Japan Joint Workshop on Algorithms and Computation 31 - 39 1999年07月

一階論理式の学習と帰納論理プログラミング査読有り

有村博紀,平田耕一

人工知能学会誌 14 ( 5 ) 790 - 799 1999年04月

スキーママッチングとその計算量査読有り

山田敬三,平田耕一,原尾政輝

電子情報通信学会論文誌 J82-D-I ( 11 ) 1307 - 1316 1999年04月

On the Hardness of Approximating the Minimum Consistent Acyclic DFA and Decision Diagram 査読有り

Shinichi Shimozono,Kouichi Hirata,Ayumi Shinohara

Information Processing Letters 66 ( 4 ) 165 - 170 1998年05月

Constructing Simply Recursive Programs from a Finite Set of Good Examples 査読有り

平田　耕一

Information Processing Letters 64 225 - 230 1997年12月

型付ラムダ計算における証明文法査読有り

山田敬三,平田耕一,原尾政輝

電子情報通信学会論文誌 J80-D-I ( 11 ) 866 - 879 1997年04月

Constructive Learning of Translations Based on Dictionaries 査読有り

Noriko Sugimoto,Kouichi Hirata,Hiroki Ishizaka

Proc. 7th International Workshop on Algorithmic Learning Theory (ALT'96), Lecture Notes in Artificial Intelligence 1160 1996年10月

On the Hardness of Approximating the Minimum Consistent OBDD Problems 査読有り

Kouichi Hirata,Shinichi Shimozono,Ayumi Shinohara

Proc. 5th Scandinavian Workshop on Algorithm Theory (SWAT'96), Lecture Notes in Computer Science 1097 1996年08月

Rule-Generating Abduction for Recursive Prolog 査読有り

平田　耕一

Informatica 20 ( 1 ) 43 - 55 1996年04月

A Classification of Abduction: Abduction for Logic Programming 査読有り

平田　耕一

Machine Intelligence 14 297 - 424 1995年04月

Rule-Generating Abduction for Recursive Prolog 査読有り

平田　耕一

Proc. 4th Internaitonal Workshop on Analogical and Inductive Inference (AII'94), Lecture Notes in Artificial Intelligence 872 1994年10月

Stable Model Semantics of Circumscription 査読有り

平田　耕一

Bulletin of Informatics and Cybernetics 26 ( 1-2 ) 1994年04月

On Russian Propositions 査読有り

平田　耕一

Bulletin of Informatics and Cybernetics 25 ( 1-2 ) 1992年04月

　前のページ-次のページ　

<平田 耕一>

論文 - 平田 耕一

<平田　耕一>

論文 - 平田　耕一