学会発表・論文
-
Data Science and Big Data Analytics (DSBDA), IEEE International Conference on Data Mining Workshop (ICDMW 2018)
An Extension of Gradient Boosted Decision Tree Incorporating Statistical Tests
Ryuji Sakata, Iku Ohama, Tadahiro Taniguchi
Link: https://ieeexplore.ieee.org/document/8637438 -
Transactions of the Japanese Society for Artificial Intelligence (JSAI)
Discovering Relevance-Dependent Bicluster Structure from Relational Data: A Model and Algorithm
Iku Ohama, Takuya Kida, Hiroki Arimura
Link: https://www.jstage.jst.go.jp/article/tjsai/33/6/33_B-I46/_article/-char/ja -
IEICE Transactions on Information and Systems, E101.D (2018)
Discovering Co-cluster Structure from Relationships between Biased Objects
Iku Ohama, Takuya Kida, Hiroki Arimura
Link: https://www.jstage.jst.go.jp/article/transinf/E101.D/12/E101.D_2017EDP7195/_article/-char/ja -
The 31st Annual Conference on Neural Information Processing Systems (NIPS 2017)
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Iku Ohama, Issei Sato, Takuya Kida, Hiroki Arimura
Link: https://papers.nips.cc/paper/6643-on-the-model-shrinkage-effect-of-gamma-process-edge-partition-models.pdf -
International Joint Conferences on Artificial Intelligence (IJCAI) 2017
Discovering Relevance-Dependent Bicluster Structure from Relational Data
Iku Ohama, Takuya Kida, Hiroki Arimura
Link: https://www.ijcai.org/Proceedings/2017/0359.pdf -
IEICE Transactions on Information and Systems Vol.E99.D (2016) Issue 4
The Relevance Dependent Infinite Relational Model for Discovering Co-cluster Structure from Relationships with Structured Noise
Iku Ohama, Hiromi Iida, Takuya Kida, Hiroki Arimura
Link: https://www.jstage.jst.go.jp/article/transinf/E99.D/4/E99.D_2015EDP7329/_article/-char/ja/ -
Ubicomp '15 Workshop: Workshop on Mobile and Situated Crowdsourcing (WMSC2015)
A Machine Learning Approach for Lighting Perception Analysis via Crowdsourcing
Yuki Minoda, Iku Ohama, Eiichi Muramoto
Link: http://dl.acm.org/citation.cfm?id=2800969 -
2015 SIAM International Conference on DATA MINING (SDM) 2015
Multi-Layered Framework for Modeling Relationships between Biased Objects
Iku Ohama, Takuya Kida, Hiroki Arimura
Link: http://epubs.siam.org/doi/abs/10.1137/1.9781611974010.92
講演・記事・出版
-
Authority Magazine（2022/11/14）
Panasonic’s Dr Iku Ohama On The Future Of Artificial Intelligence