Mr. Quentin Jodelet (a doctoral student of our laboratory) was in the top 4
challenge winners (among 79 teams) of
CVPR Challenge on Continual Learning on June 14.(2020.6.15)
Our work appear in
attempts for AI research for COVID-19 of
AI Japan R&D Network:
accurate decision of emergency transport hospitals using graph deep learning and
centrality of temporal networks for preventing the spread of infection (in Japanese) (2020.6.1)
Further updates: Because of the pandemic of COVID-19, we will use
this informal site for further updates for a while. (2020.3.30)
Ohmsha decided to print some more copies of the book (
"Learning Network Analysis with Python" (in Japanese)) written by Murata. (2020.2.21)
Murata gave a talk as
an invited speaker of
MARAMI 2019 (title :
Deep Learning Approaches for Networks (slides)). (2019.11.7)
Murata gave a talk as an invited speaker of
a meeting of Plasma Electronics at Tohoku University. (
slides (in Japanese)). (2019.9.25)
Murata published a book "Learning Network Analysis with Python" (
bibliographic info & program codes /
Ohmsha (publisher) /
Amazon). (2019.9.15)
A paper (Title:
"Recurrent Translation-based Network for Top-N Sparse Sequential Recommendation") written by Mr. Nuttapong Chairatanakul (first grade of doctoral course student), Dr. Liu Xin (AIRC, AIST) and Murata is accepted by
IEEE Access (impact factor : 4.098). (2019.8.22)
A paper (Title:"Fast Approximations of Betweenness Centrality using Graph Neural Networks") written by Mr. Sunil Kumar Maurya (first grade of doctoral course student), Dr. Liu Xin (AIRC, AIST) and Murata is accepted as a short paper of
CIKM 2019 (acceptance rate:21%). (2019.8.9)
Mr. Hibiki Taguchi receives
JSAI Annual Conference Award (Oral Presentation) for his presentation (title:
"Community detection in bipartite networks by multi label propagation algorithm") at
The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, 2019. (2019.8.1)
Mr. Makoto Tachibana received
JSAI Incentive Award for his presentation (title:
"Semi-supervised learning on network using structure features and graph convolution" (in Japanese)) at
the 115th SIG meeting on Knowledge Base Systems. (2019.6.27)
Murata gave a talk (title:
"Deep Learning Approaches for Eruption Prediction of Sakurajima") as an invited speaker of
"Potentiality of Machine Learning in Solid Earth Sciences" session of
JpGU Meeting 2019. (2019.5.26)
Murata gave a lecture on
"Introduction of network analysis with Google Colaboratory" as one of the AI tool introduction of
JSAI (
codes and slides here). (2019.5.23)
Murata gave a talk (title:
"Deep Learning Approaches for Eruption Prediction of Sakurajima") as an invited speaker of
115th SIG-KBS meeting of JSAI. (2018.11.23)
Mr. Hiep Le's work of the prediction of volcanic eruption of Sakurajima appeared in an article of
monthly magazine Fole (in Japanese) issued by Mizuho Research Institute in October 2018. (2018.9.27)
A paper (Title:
"Learning Community Structure with Variational Autoencoder") written by Mr. Choong Jun Jin (second grade of doctoral course student), Dr. Liu Xin (AIRC, AIST) and Murata is accepted as a full paper of
IEEE ICDM 2018 (acceptance rate:8.86%). (2018.8.20)
Murata taught an intensive lecture on
Complex Networks at
Shanghai University of Finance and Economics. (2018.7.12-17)
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)
