Ian Osband
TalkRL: The Reinforcement Learning Podcast
Understanding Joint Predictions in Machine Learning
Exploring the significance of joint predictive distributions versus marginal predictions in machine learning, highlighting how multiple predictions based on multiple inputs can impact decision-making processes. Examples like image classification and coin flipping are used to illustrate the concept and its implications on outcome probabilities.
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