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Faculty of Business, Data Sciences and Operations Department, Lingnan University, University of Southern California
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CART random forests, often treated as black boxes, are surprisingly amenable to stochastic control analysis, revealing a tension between local stability and global optimality.
Transfer learning gets a boost: SMART sidesteps restrictive assumptions and data sharing limitations by transferring spectral information between tasks, leading to improved accuracy and robustness.