Mr. Hiep Le's paper (Title: "Deep Modular Multimodal Fusion on Multiple Sensors for Volcano Activity Recognition") has been accepted by
ECML-PKDD 2018 (acceptance rate:27%). (2018.6.19)
Mr. Hiep Le's research on predicting volcanic eruptions of Sakurajima (presented at
JSAI 2018 on June 6, 2018) appeared in a local TV news of NHK Kagoshima and in an atricle of South Japan Newspaper (2018.6.7)
"Kagoshima NEWS WEB -- AI predicts eruptions of Sakurajima" (NHK Kagoshima, in Japanese)
"AI predicts eruptions of Sakurajima --- 51.9% accuracy achieved with four-stage warning system by research team of Tokyo Tech & Kyoto Univ." (South Japan Newspaper Company, in Japanese)
An article about Mr. Hiep Le's work on Sakurajima volcanic activity recognition appeared in Nikkei Newspaper (page 9) on Jan. 15, 2018. (2018.1.15)
"Tokyo Tech & Kyoto Univ. use AI for volcano activity recognition (Nikkei Newspaper (written in Japanese))" "Deep Learning Approach for Volcano Activity Recognition (News of the Dept. of CS (written in Japanese))" "Deep Learning Approach for Volcano Activity Recognition (link to an article of KBS meeting in Nov. 2017(written in Japanese))"
call for postdocs: Our laboratory takes part in
RWBC-OIL(AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory).
RWBC-OIL is a joint laboratory of Tokyo Tech and
AIST for the analysis of real-world big data started from Feb. 2017 (
news from Tokyo Tech (in Japanese),
news from AIST (in Japanese)).
RWBC-OIL hires researchers of machine learning / deep learning / graph mining / high performance computing. Please read
call for postdocs (in Japanese) for more information. If you are interested in, please contact
Murata. (2017.4.6)
Mr. Yohei Oonuki receives
JSAI Incentive Award for his presentation (title:
"Prediction of relations among RDF entities by DNN" (in Japanese)) at
the 41st SIG meeting on Semantic Web and Ontology. (2017.5.8)
Mr. Shun Nukui received
JSAI Annual Conference Student Incentive Award for his presentation (title:
"Constrained community detection based on semi-supervised non-negative matrix factorization on TensorFlow" (in Japanese)) at
2016 JSAI Annual Conference. (2017.3.1)
Murata was invited to
MARAMI 2016 as an invited speaker, but the talk was canceled. (2016.10.14)
Murata gave a talk ("Mining and learning on heterogeneous networks") as an invited speaker at
WIMS 2016 (
slides). (2016.6.15)
Dr. Xin Liu and Mr. Weichu Liu's paper (title: "Community Detection in Multi-Partite Multi-Relational Networks Based on Information Compression") was accepted by
New Generation Computing. (2016.3.7)
Mr. Phiradet Bangcharoensap's paper (title:
"Transductive Classification on Heterogeneous Information Networks with Edge Betweenness-based Normalization") was accepted by
WSDM 2016 conference (acceptance rate: 18.2%). (2015.10.14)
Mr. Phiradet Bangcharoensap's paper (title:
"Two step graph-based semi-supervised learning for online auction fraud detection") was accepted by
ECML-PKDD 2015 conference (acceptance rate: 28.6%). (2015.6.3)
Mr. Keisuke Nakata presented his work at
CompleNet 2015(the 6th Workshop on Complex Networks). His photo is
here. (2015.3.25)
Mr. Keisuke Nakata (title:
"Speeding-up of Constrained Community Detection and Development of its Interactive Environment") received
JSAI Annual Conference Award. 19 papers were selected out of 584 papers. (2014.7.22)
Dr. Xin Liu and Mr. Weichu Liu's paper (A Framework for Community Detection in Heterogeneous Multi-Relational Networks) was accepted by
Advances in Complex Systems.(2014.7.9)
Dr. Xin Liu's paper (Detecting network communities beyond assortativity-related attributes) was accepted by
Physical Review E.(2014.6.19)
Mr. Ikematsu's programs for detecting communities from n-partite networks are
available online.
Reference:"Improvement of a Tripartite Modularity and Its Optimization Method"(written in Japanese)
(Transactions of the Japanese Society for Artificial Intelligence, Vol.29, No.2, pp.245-258, 2014)(2014.2.20)
