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pro vyhledávání: '"Karthikeyan, Ajaykrishna"'
Decision trees provide a rich family of highly non-linear but efficient models, due to which they continue to be the go-to family of predictive models by practitioners across domains. But learning trees is challenging due to their discrete decision b
Externí odkaz:
http://arxiv.org/abs/2102.07567
Autor:
Natarajan, Nagarajan, Karthikeyan, Ajaykrishna, Jain, Prateek, Radicek, Ivan, Rajamani, Sriram, Gulwani, Sumit, Gehrke, Johannes
We formalize and study ``programming by rewards'' (PBR), a new approach for specifying and synthesizing subroutines for optimizing some quantitative metric such as performance, resource utilization, or correctness over a benchmark. A PBR specificatio
Externí odkaz:
http://arxiv.org/abs/2007.06835