Fusing Loop Detector and Probe Vehicle Data to Estimate Travel Time Statistics on Signalized Urban Networks

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Mechanism design theory examines the design of allocation mechanisms or incentive systems involving multiple rational but self-interested agents and plays a central role in many societally important problems in economics. In mechanism design problems, agen ...

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We introduce a distributionally robust maximum likelihood estimation model with a Wasserstein ambiguity set to infer the inverse covariance matrix of a p-dimensional Gaussian random vector from n independent samples. The proposed model minimizes the worst ...

Fusing Loop Detector and Probe Vehicle Data to Estimate Travel Time Statistics on Signalized Urban Networks

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Distributional Robustness in Mechanism Design

Sequential Outlier Detection Based on Incremental Decision Trees

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Collaborative Sampling in Generative Adversarial Networks

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Global turbulence features across marginality and non-local pedestal-core interactions

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Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator