Publication
I'm a bit lazy to update my publication list. So please have a look at DBLP for recent publications.
Journal Paper (Refereed)
Investigating Word Vectors for the Negation of Verbs
Tomoya Sasaki, Yuto Kikuchi, Kazuo Hara and Ikumi Suzuki
SN computer Science, Vol.5, No. 222, Springer Nature, 2024.Study on visual machine-learning on the omnidirectional transporting robot
Adrian Zambrano, Kazuki Abe, Ikumi Suzuki, Theo Combelles, Kenjiro Tadakuma and Riichiro Tadakuma
Advanced Robotics, 34(13), pp.917-930, 2020.
Reducing Hub Translation Candidates Improves the Accuracy of. Bilingual Lexicon Extraction from Comparable Corpora
Yutaro Shigeto, Ikumi Suzuki, Kazuo Hara, Masashi Shimbo and Yuji Matsumoto
Journal of Japanese Society of Artificial Intelligence, Vol. 31, No.2 p.E-F43_1-12, 2016
Computation of Contextual Word Similarity Exploiting Syntactic and SemanticStructural Co-occurrences
Kazuo Hara, Ikumi Suzuki, Masashi Shimbo and Yuji Matsumoto
Journal of Japanese Society of Artificial Intelligence, Vol.28, No.4, pp.379-390, 2013. (in Japanese)
Reducing Hubs with Laplacian-based Kernels
Ikumi Suzuki, Kazuo Hara, Masashi Shimbo and Yuji Matsumoto
Journal of Japanese Society of Artificial Intelligence, Vol.28, No.3, pp.297-310, 2013. (in Japanese)
Robust Model Selection for Classification of Microarrays.
Ikumi Suzuki, Takashi Takenouchi, Miki Ohira, Shigeyuki Oba, and Shin Ishii.
Cancer Informatics, Vol.7, pp.141-157, June 2009
International Conference/Workshop (Refereed)
[IEEE BigData 21] Bayesian Optimization With an Auxiliary Classifier for the Development of Polymer Materials.
Tomoya Sasaki, Arisa Nakamura, Jun-Ichi Harasawa, Kazuo Hara, Ikumi Suzuki, Tatsuhiro Takahashi．
2021 IEEE International Conference on Big Data (Big Data), pp. 6014-6016, Orlando, FL, USA (2021.12).[IEEE BigData 21] Robust Method to Convert HIRAGANA Sequences into Japanese Text.
Toshiki Yamaguchi, Kazuo Hara, Ikumi Suzuki.
2021 IEEE International Conference on Big Data (Big Data), pp.6058-6060, Orlando, FL, USA (2021.12).[DATA 21] Impact of Duplicating Small Training Data On GANs
Yuki Eizuka, Kazuo Hara, Ikumi Suzuki.
In proceedings of 10th International Conference on Data Science, Technology and Applications (DATA 2021), pp.71-78, Online Streaming, (2021.7).[DATA 21] Semantic Entanglement On Verb Negation
Yuto Kikuchi, Kazuo Hara, Ikumi Suzuki.
In proceedings of 10th International Conference on Data Science, Technology and Applications (DATA 2021), pp.71-78, Online Streaming, (2021.7).[KDIR 20] Target Evaluation for Neural Language Model using Japanese Case Frame
Kazuhito Tamura, Ikumi Suzuki, Kazuo Hara
In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR 2020), pp 251-258, Budapest, Hungary, November 2-4, 2020[Romansy 20] Developing a Flexible Segment Unit for Redun-dant-DOF Manipulator using Bending Type Pneumatic Artificial Muscle
Hiroki Tomori, Tomohiro Koyama, Hiromitsu Nishikata, Akinori Hayasaka and Ikumi Suzuki
23rd CISM IFToMM Symposium on Robot Design, Dynamics and Control,pp.xxx-xxx, September 20-24, 2020 Sapporo, Japan[SIGIR 17] Centered kNN Graph for Semi-Supervised Learning
Ikumi Suzuki and Kazuo Hara
In proceedings of the 40th Annual ACM SIGIR Conference, pp.857-860, Tokyo 2017
SIGIR is the top international conference in the field of Information Retrieval (IR). Accepted as a short paper, the acceptance rate is 30%)
[AAAI 16] Flattening the Density Gradient for Eliminating Spatial Centrality to Reduce Hubness
Kazuo Hara*, Ikumi Suzuki*, Kei Kobayashi, Kenji Fukumizu and Miloš Radovanović
In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), pp.1659-1665, Arizona, Phoenix, USA, February 2016.
* Equally contributed (AAAI is the top international conference in the field of Artificial Intelligence and Machine Learning. Accepted as a Full paper, the acceptance rate is 26%)
[SISAP 15] Reducing Hubness for Kernel Regression
Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu and Miloš Radovanović
In Proc. the 8th International Conference on Similarity Search and Applications (SISAP), pp.339-344, Glasgow, UK, 2015
[SIGIR 15] Reducing Hubness: A Cause of Vulnerability in Recommender Systems
Kazuo Hara, Ikumi Suzuki, Kei Kobayashi and Kenji Fukumizu
In proceedings of the 38th Annual ACM SIGIR Conference, pp. 815-818, Santiago de Chile, August 2015
SIGIR is the top international conference in the field of Information Retrieval (IR). Accepted as a short paper, the acceptance rate is 31%)
[AAAI 15] Localized Centering: Reducing Hubness in Large-Sample Data.
Kazuo Hara*, Ikumi Suzuki*, Masashi Shimbo, Kei Kobayashi, Kenji Fukumizu, Miloš Radovanović
In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), pp.2645-2651, Texas, Austin, USA, January 2015
* Equally contributed (AAAI is the top international conference in the field of Artificial Intelligence and Machine Learning. Accepted as a Full paper, the acceptance rate is 26%)
[ECML/PKDD 15] Ridge Regression, Hubness, and Zero-Shot Learning
Yutaro Shigeto, Ikumi Suzuki, Kazuo Hara, Masashi Shimbo and Yuji Matsumoto
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp.135-151, 2015. Acceptance rate 23%.
[KDIR 14] Annotating Cohesive Statements of Anatomical Knowledge Toward Semi-automated Information Extraction
Kazuo Hara, Ikumi Suzuki, Kousaku Okubo and Isamu Muto
In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR), pp.342-347, Roma, Italy, October 2014
[EMNLP 13] Centering Similarity Measures to Reduce Hubs
Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Marco Saerens, Kenji Fukumizu
In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Long Papers, pp.613-623, Seattle, USA, October, 2013.
(EMNLP is the top international conference in the field of Natural Language Processing. Accepted as a Long Paper, the acceptance rate is 28%)
[COLING 12] Walk-based Computation of Contextual Word Similarity
Kazuo Hara, Ikumi Suzuki, Masashi Shimbo, Yuji Matsumoto
In Proceedings of the 24rd International Conference on Computational Linguistics (COLING). Mumbai, India, Long Papers(oral), pp.1081-1096, December 2012.
(COLING is the top international conference in the field of Natural Language Processing. Accepted as a Long paper, the acceptance rate is 25%)
[AAAI 12] Investigating the Effectiveness of Laplacian-based Kernels in Hub Reduction
Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto, Marco Saerens
In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI), pp.1112-1118, Toronto, Ontario, Canada, July 2012
(AAAI is the top international conference in the field of Artificial Intelligence and Machine Learning. Accepted as a Full paper, the acceptance rate is 26%)
[DTMBIO 09] A Graph-based Approach for Biomedical Thesaurus Expansion
Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, and Yuji Matsumoto
In Proceedings of the ACM Third International Workshop on Data and Text Mining in Bioinformatics (DTMBIO), Short Papers, pp.79-82. Hong Kong, November 2009
[GIW 05] A Selection Criterion for Robust Classifiers: Cancer Prognosis with Microarray Gene Expression
Ikumi Suzuki, Shigeyuki Oba, and Shin Ishii
Genome Informatics Workshop (GIW), 2005
Domestic Conference (研究会等, not refereed）
日本語格フレームを用いた言語モデルの評価
田村和仁，原一夫，鈴木郁美
第34回 人工知能学会全国大会, 1D5-GS-9-01 pp.1-4, 9th-12th Jun 2020, 熊本．湾曲型空気圧ゴム人工筋肉を用いた冗長マニピュレータの開発
西方宏光, 小山知洋, 早坂昭慶, 戸森央貴, 鈴木郁美
日本機械学会ロボティクス・メカトロニクス2020 講演論文集, 1A1-J062020,pp.1-4,27th-30th May, 2020, 金沢Generating Serif for Characters
Kazuhito. Tamura, Kazuo Hara and Ikumi Suzuki
APSCIT 2018, July 19-22, Sapporo, JAPAN.
Won The 3rd prize poster presentation
鈴木郁美, 原一夫, 新保仁 情報処理学会研究報告 第209回自然言語処理研究会, Vol.2012-NL-209 No.11, pp.1-8, November 2012.
鈴木郁美, 原一夫, 新保仁, 松本裕治
第14回 電子情報通信学会 情報論的学習理論と機械学習研究会（IBISML）
信学技報, vol. 111, no. 275, IBISML2011-80, pp. 257-262, November 2011.
バイオ医療専門用語のシソーラス拡張のための分布類似度計算法の提案
鈴木郁美, 原一夫, 新保仁, 松本裕治
第33回日本分子生物学会年会・第83回日本生化学会大会合同大会(BMB2010), December 2010.
鈴木郁美，原一夫，新保仁，松本裕治
情報処理学会研究報告 第199回自然言語処理研究会, Vol.2010-NL-199 No.1, pp.1-6, November 2010.
コーパスに出現するライフサイエンス分野の専門用語の同定とシソーラスへのマッピング
原一夫, 鈴木郁美, 新保仁, 松本裕治
シンポジウム 「ライフサイエンスの未来へ～10年先のデータベースを考える～」, 5 October 2010.
バイオ医療専門用語の類義語獲得
鈴木郁美, 原一夫, 新保仁, 松本裕治
文部科学省委託研究開発事業 統合データベースプロジェクト シンポジウム 2009 「データベースが拓くこれからのライフサイエンス」, 12 June 2009.
鈴木郁美, 原一夫, 新保仁, 松本裕治
情報処理学会研究報告, 情報学基礎自然言語処理合同研究会, 2009-FI-93, 2009-NL-189, pp.65-70, January 2009.
二村好憲, 大平美紀, 鈴木郁美, 大羽成征, 石井信, 富岡伸元, 檜山英三, 松永正訓, 林富, 安藤久實, 水田祥代, 堀江弘, 金子道夫, 佐々木文章, 橋都浩平, 大沼直躬,
肝芽腫におけるアレイCGH・cDNAマイクロアレイの解析： 肝芽腫予後診断チップの開発へ向けた試み,
小児がん : 小児悪性腫瘍研究会記録. Vol.43，No.2, pp.263, September 2006.
二村好憲, 鈴木郁美, 富岡伸元, 大羽成征, 大平美紀, 藤堂省, 松永正訓, 林富, 安藤久實, 田口智章, 堀江弘, 金子道夫, 橋都浩平, 佐々木文章, 大沼直躬, 檜山英三, 好田忠行, Feuerstein Burt, 石井信, 中川原章,
肝芽腫におけるアレイCGH・cDNAマイクロアレイ解析,
小児がん : 小児悪性腫瘍研究会記録, Vol.43, No.3, 24OP6-4, pp.553, November 2006.
鈴木郁美, 大羽成征, 平山淳一郎, 石井信
信学技報, NLP2005-66, NC2005-58, pp.25-30.