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cs.LG2023
Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach
Arman Rahbar, Niklas Åkerblom, Morteza Haghir Chehreghani
Online decision making plays a crucial role in numerous real-world applications. In many scenarios, the decision is made based on performing a sequence of tests on the incoming dat…
cs.LG2023
Efficient Online Decision Tree Learning with Active Feature Acquisition
Arman Rahbar, Ziyu Ye, Yuxin Chen +1
Constructing decision trees online is a classical machine learning problem. Existing works often assume that features are readily available for each incoming data point. However, i…