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Data Mining Technology Group

The Data Mining Technology Group in NEC Data Science Research Laboratories
is trying to realize a brighter world using data analytics.

Our purpose is to predict the future and optimize an entire society based on data accumulated in the real world.
We are developing data analytics technologies by using mathematical techniques such as machine learning, statistics and optimization, and are conducting commercialization of those technologies.


Recent Publication

  • Zhao Song, Yusuke Muraoka, Ryohei Fujimaki, Lawrence Carin, Scalable Model Selection for Belief Networks, Thirty-first Annual Conference on Neural Information Processing Systems (NIPS), 2017
  • Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi, Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation, Thirty-first Annual Conference on Neural Information Processing Systems (NIPS), 2017
  • Masafumi Oyamada, Shinji Nakadai, Relational Mixture of Experts: Explainable Demographics Prediction with Behavioral Data, IEEE International Conference on Data Mining (ICDM), 2017
  • Chunchen Liu, Feng Lu, Ryohei Fujimaki, Streaming Model Selection via Online Factorized Asymptotic Bayesian Inference, IEEE International Conference on Data Mining (ICDM), 2016
  • Ito and Fujimaki, Large-scale Price Optimization via Network Flow, Annual Conference on Neural Information Processing Systems (NIPS), 2016.
  • Haichuan Yang, Ryohei Fujimaki, Yukitaka Kusumura, Ji Liu, "Online Feature Selection: A Limited-Memory Substitution Algorithm and its Asynchronous Parallel Variation", Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016
  • Masato Asahara, Ryohei Fujimaki, "Distributed Heterogeneous Mixture Learning On Spark", Spark Summit 2016.
  • Masato Asahara, Ryohei Fujimaki, "Big Data Heterogeneous Mixture Learning on Spark", Hadoop Summit San Jose, 2016.


For any questions regarding our data mining technologies or this web page, please

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