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Masashi Shimbo
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2020 – today
- 2024
- [c38]Yuta Mukobara, Yutaro Shigeto, Masashi Shimbo:
Rethinking Loss Functions for Fact Verification. EACL (2) 2024: 432-442 - [i14]Yuta Mukobara, Yutaro Shigeto, Masashi Shimbo:
Rethinking Loss Functions for Fact Verification. CoRR abs/2403.08174 (2024) - 2023
- [j9]Yuya Yoshikawa
, Yutaro Shigeto
Action class relation detection and classification across multiple video datasets. Pattern Recognit. Lett. 173: 93-100 (2023) - [j8]Katsuhiko Hayashi
Binarized Embeddings for Fast, Space-Efficient Knowledge Graph Completion. IEEE Trans. Knowl. Data Eng. 35(1): 141-153 (2023) - [c37]Yutaro Shigeto, Masashi Shimbo, Yuya Yoshikawa, Akikazu Takeuchi:
Learning Decorrelated Representations Efficiently Using Fast Fourier Transform. CVPR 2023: 2052-2060 - [i13]Yutaro Shigeto, Masashi Shimbo, Yuya Yoshikawa, Akikazu Takeuchi:
Learning Decorrelated Representations Efficiently Using Fast Fourier Transform. CoRR abs/2301.01569 (2023) - [i12]Yuya Yoshikawa, Yutaro Shigeto, Masashi Shimbo, Akikazu Takeuchi:
Action Class Relation Detection and Classification Across Multiple Video Datasets. CoRR abs/2308.07558 (2023) - 2021
- [c36]Yushi Hirose, Masashi Shimbo, Taro Watanabe:
Transductive Data Augmentation with Relational Path Rule Mining for Knowledge Graph Embedding. ICBK 2021: 377-384 - [i11]Yushi Hirose, Masashi Shimbo, Taro Watanabe:
Transductive Data Augmentation with Relational Path Rule Mining for Knowledge Graph Embedding. CoRR abs/2111.00974 (2021) - 2020
- [c35]Katsuhiko Hayashi, Koki Kishimoto, Masashi Shimbo:
A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings. EMNLP (Findings) 2020: 109-114
2010 – 2019
- 2019
- [j7]Van-Thuy Phi
Distant Supervision for Relation Extraction via Piecewise Attention and Bag-Level Contextual Inference. IEEE Access 7: 103570-103582 (2019) - [c34]Koki Kishimoto, Katsuhiko Hayashi, Genki Akai, Masashi Shimbo, Kazunori Komatani:
Binarized Knowledge Graph Embeddings. ECIR (1) 2019: 181-196 - [c33]Katsuhiko Hayashi, Masashi Shimbo:
A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs. EMNLP/IJCNLP (1) 2019: 2422-2430 - [i10]Koki Kishimoto, Katsuhiko Hayashi, Genki Akai, Masashi Shimbo, Kazunori Komatani:
Binarized Knowledge Graph Embeddings. CoRR abs/1902.02970 (2019) - [i9]Katsuhiko Hayashi, Masashi Shimbo:
A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs. CoRR abs/1909.01567 (2019) - [i8]Koki Kishimoto, Katsuhiko Hayashi, Genki Akai, Masashi Shimbo:
Binarized Canonical Polyadic Decomposition for Knowledge Graph Completion. CoRR abs/1912.02686 (2019) - 2018
- [c32]Hitoshi Manabe, Katsuhiko Hayashi, Masashi Shimbo:
Data-Dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion. AAAI 2018: 3754-3761 - [c31]Van-Thuy Phi, Joan Santoso
Ranking-Based Automatic Seed Selection and Noise Reduction for Weakly Supervised Relation Extraction. ACL (2) 2018: 89-95 - [c30]Yuta Kobayashi, Masashi Shimbo, Yuji Matsumoto:
Citation Recommendation Using Distributed Representation of Discourse Facets in Scientific Articles. JCDL 2018: 243-251 - [c29]Takahiro Ishihara, Katsuhiko Hayashi, Hitoshi Manabe, Masashi Shimbo, Masaaki Nagata:
Neural Tensor Networks with Diagonal Slice Matrices. NAACL-HLT 2018: 506-515 - [i7]Yutaro Shigeto, Masashi Shimbo, Yuji Matsumoto:
A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs. CoRR abs/1806.03945 (2018) - [i6]Hitoshi Manabe, Katsuhiko Hayashi, Masashi Shimbo:
Data-dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion. CoRR abs/1808.08361 (2018) - 2017
- [c28]Katsuhiko Hayashi, Masashi Shimbo:
On the Equivalence of Holographic and Complex Embeddings for Link Prediction. ACL (2) 2017: 554-559 - [c27]Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, Yuji Matsumoto:
Knowledge Transfer for Out-of-Knowledge-Base Entities : A Graph Neural Network Approach. IJCAI 2017: 1802-1808 - [c26]Yutaro Shigeto, Masashi Shimbo, Yuji Matsumoto:
A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs. PAKDD (1) 2017: 17-29 - [i5]Katsuhiko Hayashi, Masashi Shimbo:
On the Equivalence of Holographic and Complex Embeddings for Link Prediction. CoRR abs/1702.05563 (2017) - [i4]Ai Azuma, Masashi Shimbo, Yuji Matsumoto:
An Algebraic Formalization of Forward and Forward-backward Algorithms. CoRR abs/1702.06941 (2017) - [i3]Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, Yuji Matsumoto:
Knowledge Transfer for Out-of-Knowledge-Base Entities: A Graph Neural Network Approach. CoRR abs/1706.05674 (2017) - 2016
- [c25]Masashi Tsubaki, Kevin Duh, Masashi Shimbo, Yuji Matsumoto:
Non-Linear Similarity Learning for Compositionality. AAAI 2016: 2828-2834 - 2015
- [c24]Kazuo Hara, Ikumi Suzuki, Masashi Shimbo, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic:
Localized Centering: Reducing Hubness in Large-Sample Data. AAAI 2015: 2645-2651 - [c23]Akifumi Yoshimoto, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto:
Coordination-Aware Dependency Parsing (Preliminary Report). IWPT 2015: 66-70 - [c22]Yutaro Shigeto, Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto:
Ridge Regression, Hubness, and Zero-Shot Learning. ECML/PKDD (1) 2015: 135-151 - [i2]Yutaro Shigeto, Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto:
Ridge Regression, Hubness, and Zero-Shot Learning. CoRR abs/1507.00825 (2015) - 2014
- [j6]Mathieu Senelle, Silvia García-Díez, Amin Mantrach, Masashi Shimbo, Marco Saerens, François Fouss
The Sum-over-Forests Density Index: Identifying Dense Regions in a Graph. IEEE Trans. Pattern Anal. Mach. Intell. 36(6): 1268-1274 (2014) - 2013
- [c21]Masashi Tsubaki, Kevin Duh, Masashi Shimbo, Yuji Matsumoto:
Modeling and Learning Semantic Co-Compositionality through Prototype Projections and Neural Networks. EMNLP 2013: 130-140 - [c20]Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Marco Saerens, Kenji Fukumizu:
Centering Similarity Measures to Reduce Hubs. EMNLP 2013: 613-623 - [i1]Mathieu Senelle, Silvia García-Díez, Amin Mantrach, Masashi Shimbo, Marco Saerens, François Fouss:
The Sum-over-Forests density index: identifying dense regions in a graph. CoRR abs/1301.0725 (2013) - 2012
- [c19]Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto, Marco Saerens:
Investigating the Effectiveness of Laplacian-Based Kernels in Hub Reduction. AAAI 2012: 1112-1118 - [c18]Kazuo Hara, Ikumi Suzuki, Masashi Shimbo, Yuji Matsumoto:
Walk-based Computation of Contextual Word Similarity. COLING 2012: 1081-1096 - 2011
- [j5]Silvia García-Díez, François Fouss
A sum-over-paths extension of edit distances accounting for all sequence alignments. Pattern Recognit. 44(6): 1172-1182 (2011) - [j4]Amin Mantrach, Nicolas van Zeebroeck
Semi-supervised classification and betweenness computation on large, sparse, directed graphs. Pattern Recognit. 44(6): 1212-1224 (2011) - [c17]Tetsuo Kiso, Masashi Shimbo, Mamoru Komachi, Yuji Matsumoto:
HITS-based Seed Selection and Stop List Construction for Bootstrapping. ACL (2) 2011: 30-36 - [c16]Kohei Ozaki, Masashi Shimbo, Mamoru Komachi, Yuji Matsumoto:
Using the Mutual k-Nearest Neighbor Graphs for Semi-supervised Classification on Natural Language Data. CoNLL 2011: 154-162 - 2010
- [j3]Amin Mantrach, Luh Yen, Jérôme Callut, Kevin Françoisse, Masashi Shimbo, Marco Saerens:
The Sum-over-Paths Covariance Kernel: A Novel Covariance Measure between Nodes of a Directed Graph. IEEE Trans. Pattern Anal. Mach. Intell. 32(6): 1112-1126 (2010) - [c15]Silvia García-Díez, François Fouss
Normalized Sum-over-Paths Edit Distances. ICPR 2010: 1044-1047
2000 – 2009
- 2009
- [j2]Masashi Shimbo, Takahiko Ito, Daichi Mochihashi, Yuji Matsumoto:
On the properties of von Neumann kernels for link analysis. Mach. Learn. 75(1): 37-67 (2009) - [c14]Hideharu Okuma, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto:
Bypassed alignment graph for learning coordination in Japanese sentences. ACL/IJCNLP (2) 2009: 5-8 - [c13]Kazuo Hara, Masashi Shimbo, Hideharu Okuma, Yuji Matsumoto:
Coordinate Structure Analysis with Global Structural Constraints and Alignment-Based Local Features. ACL/IJCNLP 2009: 967-975 - [c12]Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto:
A graph-based approach for biomedical thesaurus expansion. DTMBIO 2009: 79-82 - 2008
- [c11]Mamoru Komachi, Taku Kudo, Masashi Shimbo, Yuji Matsumoto:
Graph-based Analysis of Semantic Drift in Espresso-like Bootstrapping Algorithms. EMNLP 2008: 1011-1020 - [c10]Harendra Bhandari, Masashi Shimbo, Takahiko Ito, Yuji Matsumoto:
Generic Text Summarization Using Probabilistic Latent Semantic Indexing. IJCNLP 2008: 133-140 - [c9]Luh Yen, Marco Saerens, Amin Mantrach, Masashi Shimbo:
A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances. KDD 2008: 785-793 - 2007
- [c8]Masashi Shimbo, Kazuo Hara:
A Discriminative Learning Model for Coordinate Conjunctions. EMNLP-CoNLL 2007: 610-619 - [c7]Masashi Shimbo, Takahiko Ito, Yuji Matsumoto:
Evaluation of kernel-based link analysis measures on research paper recommendation. JCDL 2007: 354-355 - 2006
- [c6]Takahiko Ito, Masashi Shimbo, Daichi Mochihashi, Yuji Matsumoto:
Investigating the Effect of Multiple Communities on Kernel-Based Citation Analysis. ICDE Workshops 2006: 113 - [c5]Takahiko Ito, Masashi Shimbo, Daichi Mochihashi, Yuji Matsumoto:
Exploring Multiple Communities with Kernel-Based Link Analysis. PKDD 2006: 235-246 - 2005
- [c4]Takahiko Ito, Masashi Shimbo, Taku Kudo, Yuji Matsumoto:
Application of kernels to link analysis. KDD 2005: 586-592 - 2003
- [j1]Masashi Shimbo, Toru Ishida
Controlling the learning process of real-time heuristic search. Artif. Intell. 146(1): 1-41 (2003) - [c3]Masashi Shimbo, Takahiro Yamasaki, Yuji Matsumoto:
Sentence Role Identification in Medline Abstracts: Training Classifier with Structured Abstracts. Active Mining 2003: 236-254 - 2000
- [c2]Masashi Shimbo, Toru Ishida:
Towards Real-Time Search with Inadmissible Heuristics. ECAI 2000: 609-613
1990 – 1999
- 1996
- [c1]Toru Ishida, Masashi Shimbo:
Improving the Learning Efficiencies of Realtime Search. AAAI/IAAI, Vol. 1 1996: 305-310
Coauthor Index
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