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1. Decentralized advice

   https://doi.org/10.1016/j.ejpoleco.2020.101871  

   Feddersen, Timothy; Gradwohl, Ronen (June 2020, European Journal of Political Economy)
2. Queues with Small Advice

   Mitzenmacher, Michael (January 2021, SIAM Conference on Applied and Computational Discrete Algorithms)

   null (Ed.)

   Motivated by recent work on scheduling with predicted job sizes, we consider the performance of scheduling algorithms with minimal advice, namely a single bit. Besides demonstrating the power of very limited advice, such schemes are quite natural. In the prediction setting, one bit of advice can be used to model a simple prediction as to whether a job is “large” or “small”; that is, whether a job is above or below a given threshold. Further, one-bit advice schemes can correspond to mechanisms that tell whether to put a job at the front or the back for the queue, a limitation which may be useful in many implementation settings. Finally, queues with a single bit of advice have a simple enough state that they can be analyzed in the limiting mean-field analysis framework for the power of two choices. Our work follows in the path of recent work by showing that even small amounts of even possibly inaccurate information can greatly improve scheduling performance 

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3. Prediction with expert advice applied to the problem of prediction with expert advice

   https://doi.org/10.1007/s11229-022-03809-5  

   Herrmann, Daniel A. (July 2022, Synthese)

   Abstract We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in which she is not herself an expert? This question is more complex, given the messy and strategic nature of politics. In this paper we argue that the prediction with expert advice (PWEA) framework from machine learning provides helpful tools for addressing these problems. We outline conditions under which we should expert PWEA to be helpful and those under which we should not expect these methods to perform well. 

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4. Advice for the campus interview

   https://doi.org/10.1090/noti1974  

   Folsom, Amanda; Kontorovich, Alex. (November 2019, Notices of the American Mathematical Society)

   This article offers advice for the campus interview in both the research university and liberal arts college setting for early career mathematicians as a part of the Early Career Section of the Notices of the American Mathematical Society. 

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5. Single-Leg Revenue Management with Advice

   https://doi.org/10.1145/3580507.3597704  

   Balseiro, Santiago; Kroer, Christian; Kumar, Rachitesh (July 2023, EC '23: Proceedings of the 24th ACM Conference on Economics and Computation)