Stochastic Structured Prediction under Bandit Feedback

NeurIPS 2016 Artem SokolovJulia KreutzerChristopher LoStefan Riezler

Stochastic structured prediction under bandit feedback follows a learning protocol where on each of a sequence of iterations, the learner receives an input, predicts an output structure, and receives partial feedback in form of a task loss evaluation of the predicted structure. We present applications of this learning scenario to convex and non-convex objectives for structured prediction and analyze them as stochastic first-order methods... (read more)

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