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6 events found.

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  • August 2019
  • Fri 9
    9 August 2019 @ 9:30 AM - 1:30 PM SMT

    NUS National Observance Ceremony 2019

    University Hall National University of Singapore, 21 Lower Kent Ridge Rd, Singapore

    IORA took part in NUS National Day Observance Ceremony held on Thursday, 8 August 2019 at University Hall, National University of Singapore. Dr Huang Jinjia, IORA Research Fellow, presented the  […]

  • October 2019
  • Sun 20
    20 October 2019 - 23 October 2019

    INFORMS 2019

    The 2019 INFORMS Annual Meeting is a unique opportunity to connect and network with the more than 6,000 INFORMS members, students, prospective employers and employees, and academic and industry experts who compose the INFORMS community. It is […]

  • January 2021
  • Fri 15
    15 January 2021 @ 10:00 AM - 16 January 2021 @ 11:00 AM SMT

    IORA Seminar Series | 15 Jan | 10am

    Shape-constrained convex regression problem deals with fitting a convex function to the observed data, where additional constraints are imposed, such as component-wise monotonicity and uniform Lipschitz continuity. This talk presents […]

  • February 2021
  • Fri 26
    26 February 2021 @ 10:00 AM - 11:00 AM SMT

    IORA Seminar Series | 26 Feb | 10am

    Extensive research has shown that human decision makers in operations and supply chains are often influenced by cognitive biases and social preferences, and as a consequence fail to achieve the […]

  • March 2021
  • Fri 5
    5 March 2021 @ 10:00 AM - 12:00 PM SMT

    The Dao of Robustness

    We present a general framework for data-driven optimization called robustness optimization that favors solutions for which a risk-aware objective function would best attain an acceptable target even when the actual […]

  • Fri 12
    12 March 2021 @ 10:00 AM - 11:30 AM SMT

    Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression

    Dr. Ying Chen is a financial statistician and data scientist. She develops statistical modelling and machine learning methods customized for nonstationary, high frequency and large dimensional complex data such as […]

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