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AutoLTS: Automating Cycling Stress Assessment via Contrastive Learning and Spatial Post-processing
Cycling stress assessment, which quantifies cyclists' perceived stress imposed by the built environment and motor traffics, increasingly informs cycling infrastructure planning and cycling route recommendation.
Machine Learning-Augmented Optimization of Large Bilevel and Two-stage Stochastic Programs: Application to Cycling Network Design
We prove bounds on the optimality gap of the generated leader decision as measured by the original objective that considers the full follower set.
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