Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Okumura, Kyohei"'
Many organizations use algorithms that have a disparate impact, i.e., the benefits or harms of the algorithm fall disproportionately on certain social groups. Addressing an algorithm's disparate impact can be challenging, however, because it is often
Externí odkaz:
http://arxiv.org/abs/2405.04816
Evidence-based targeting has been a topic of growing interest among the practitioners of policy and business. Formulating decision-maker's policy learning as a fixed-budget best arm identification (BAI) problem with contextual information, we study a
Externí odkaz:
http://arxiv.org/abs/2401.03756
Off-policy evaluation (OPE) attempts to predict the performance of counterfactual policies using log data from a different policy. We extend its applicability by developing an OPE method for a class of both full support and deficient support logging
Externí odkaz:
http://arxiv.org/abs/2212.01925
This paper develops a framework to conduct a counterfactual analysis to regulate matching markets with regional constraints that impose lower and upper bounds on the number of matches in each region. Our work is motivated by the Japan Residency Match
Externí odkaz:
http://arxiv.org/abs/2205.14387
Algorithm designers increasingly optimize not only for accuracy, but also for the fairness of the algorithm across pre-defined groups. We study the tradeoff between fairness and accuracy for any given set of inputs to the algorithm. We propose and ch
Externí odkaz:
http://arxiv.org/abs/2112.09975