Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent
通过随机梯度下降对情境老虎机进行在线统计推断
With the fast development of big data, learning the optimal decision rule by recursively updating it and making online decisions has been easier than before. We study the online statistical inference of model parameters in a contextual bandit framework of sequential decision-making. We propose a general framework for an online and adaptive data collection environment that can update decision rules via weighted stochastic gradient descent. We allow different weighting schemes…