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NEC’s AI (Artificial Intelligence) Research

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  • 2017/01/12 Ryohei Fujimaki (Ph. D), Research Fellow appeard at the panel discussion of “Artificial Intelligence and U.S.-Japan Alliance Engagement” symposium.
  • 2016/06/24We become a sponsor of the Conference on Knowledge Discovery and Data Mining (KDD'2016).
  • 2016/04/13We released the Presentation Summary and Full Transcript of Gartner Business Intelligence & Analytics Summit.
  • 2016/03/30 We released the Flash Report of Gartner Business Intelligence & Analytics Summit.
    Further details and complete transcript of this presentation will be updated in April.
  • 2016/03/03Ryohei Fujimaki (Ph. D), Research Fellow will lead a presentation entitled “Prescriptive Analysis: the Marriage of Your Business and Data Science” on March 16th from 2:00 p.m. to 2:30 p.m. (CST) at Texas C.

    Event information: Gartner Business Intelligence & Analytics Summit
    14 - 16 March 2016 | Grapevine, TX

    Click here to view the latest information of our session.
  • 2016/02/25 NEC exhibited in Mobile World Congress 2016.
    Click here to watch the video about the customer retention solution by our big data analysis technologies called HML (Heterogeneous Mixture Learning).

Recent Publication

  • 2016/11/29Daniel Andrade, Bing Bai, Ramkumar Rajendran and Yotaro Watanabe. Analogy-based Reasoning with Memory Networks for Future Prediction. In Proceedings of the Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo) at NIPS 2016, Barcelona, Spain, 2016.
  • 2016/08/24Ito and Fujimaki, Large-scale Price Optimization via Network Flow, Annual Conference on Neural Information Processing Systems (NIPS), 2016.
  • 2016/05/12Masato Asahara, Ryohei Fujimaki, "Distributed Heterogeneous Mixture Learning On Spark", Spark Summit 2016.
  • 2016/05/12Masato Asahara, Ryohei Fujimaki, "Big Data Heterogeneous Mixture Learning on Spark", Hadoop Summit San Jose, 2016.
  • 2016/05/12Haichuan 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.
  • 2015/08/10Jialei Wang, Ryohei Fujimaki, Yosuke Motohashi, “Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models”, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2015

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