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Topic-adjusted visibility metric for scientific articles
Topic-adjusted visibility metric for scientific articles

April 2018 – NUS statistician have developed a metric that automatically accounts for citation variations in different disciplines for measuring the research merit of scientific articles.

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Unlocking the power of web text data
Unlocking the power of web text data

December 2017 – NUS statisticians have developed the Regularised Text Logistic (RTL) regression model to extract informative word features from digital text for decision-making.

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Statistical hypothesis testing for high-dimensional data
Statistical hypothesis testing for high-dimensional data

October 2017 – NUS statisticians have developed an efficient method for comparing multi-group high-dimensional data.

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A more efficient method for quantifying uncertainty
A more efficient method for quantifying uncertainty

September 2017 – NUS statistician has proposed a new Monte Carlo method that is computationally more effective for quantifying uncertainty.

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A practical optimisation algorithm for big data applications
A practical optimisation algorithm for big data applications

September 2017. NUS mathematicians have proposed improvements to a well-known optimisation algorithm to significantly boost its computational efficiency.

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Paying for “extras” in freemium products and services
Paying for “extras” in freemium products and services

August 2017 – NUS statisticians have developed a better methodology to study user behaviour for freemium products and services.

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What is the weather tomorrow?
What is the weather tomorrow?

July 2017 – NUS mathematician has revealed ways which can lead to more accurate weather predictions.

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Statistical inferences with monotone density ratio
Statistical inferences with monotone density ratio

February 2017 – NUS mathematicians have developed effective methods for modelling real-life problems with monotone density ratio conditions.

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Inference for dynamical systems
Inference for dynamical systems

February 2017 – NUS statisticians have gained insights which allow for better prediction of physical phenomena.

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Fast algorithms for quantifying uncertainty
Fast algorithms for quantifying uncertainty

January 2017 – NUS statisticians have developed a method to estimate unknown parameters efficiently for modelling complex situations.

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