3 papers
eess.SY2025
Quantifying Distribution Shift in Traffic Signal Control with Histogram-Based GEH Distance
Federico Taschin, Ozan K. Tonguz
Traffic signal control algorithms are vulnerable to distribution shift, where performance degrades under traffic conditions that differ from those seen during design or training. T…
cs.LG2025
Using Kolmogorov-Smirnov Distance for Measuring Distribution Shift in Machine Learning
Ozan K. Tonguz, Federico Taschin
One of the major problems in Machine Learning (ML) and Artificial Intelligence (AI) is the fact that the probability distribution of the test data in the real world could deviate s…
cs.AI2025
The Distribution Shift Problem in Transportation Networks using Reinforcement Learning and AI
Federico Taschin, Abderrahmane Lazaraq, Ozan K. Tonguz +1
The use of Machine Learning (ML) and Artificial Intelligence (AI) in smart transportation networks has increased significantly in the last few years. Among these ML and AI approach…