Can I read From Predictions to Decisions: The Importance of Joint Predictive Distributions on EtoBox?

From Predictions to Decisions: The Importance of Joint Predictive Distributions by Wen, Zheng; Osband, Ian; Qin, Chao; Lu, Xiuyuan; Ibrahimi, Morteza; Dwaracherla, Vikranth; Asghari, Mohammad; Van Roy, Benjamin is a scholarly article available to read on EtoBox.

What is From Predictions to Decisions: The Importance of Joint Predictive Distributions about?

A fundamental challenge for any intelligent system is prediction: given some inputs, can you predict corresponding outcomes? Most work on supervised learning has focused on producing accurate marginal predictions for each input. However, we show that for a broad class of decision problems, accurate joint predictions are required to deliver good performance. In particular, we establish several results pertaining to combinatorial decision problems, sequential predictions, and multi-armed bandits to elucidate the essential role of joint predictive distributions. Our treatment of multi-armed bandits introduces an approximate Thompson sampling algorithm and analytic techniques that lead to a new kind of regret bound.

Author

Wen, Zheng; Osband, Ian; Qin, Chao; Lu, Xiuyuan; Ibrahimi, Morteza; Dwaracherla, Vikranth; Asghari, Mohammad; Van Roy, Benjamin

Published

2021

Language

EN