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06/02/2023
Improving the generalizability and robustness of large-scale traffic signal control
A number of deep reinforcement-learning (RL) approaches propose to contr...
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09/16/2022
Covariance regression with random forests
Capturing the conditional covariances or correlations among the elements...
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08/01/2022
Model-based graph reinforcement learning for inductive traffic signal control
Most reinforcement learning methods for adaptive-traffic-signal-control ...
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06/15/2021
RFpredInterval: An R Package for Prediction Intervals with Random Forests and Boosted Forests
Like many predictive models, random forests provide a point prediction f...
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03/01/2021
Dynamic estimation with random forests for discrete-time survival data
Time-varying covariates are often available in survival studies and esti...
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11/23/2020
Conditional canonical correlation estimation based on covariates with random forests
Investigating the relationships between two sets of variables helps to u...
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05/31/2020
Ensemble Methods for Survival Data with Time-Varying Covariates
We propose two new survival forests for survival data with time-varying ...
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04/23/2020
Inference for travel time on transportation networks
Travel time is essential for making travel decisions in real-world trans...
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03/06/2020
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control
Scaling adaptive traffic-signal control involves dealing with combinator...
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03/01/2018