Trustable Machine Learning

Course Description

This short course considered the problem of obtaining reliable decisions from supervised machine learning. It attempts to summarize the current state of knowledge about how we can create machine learning classifiers that, when they make a prediction, can provide a guarantee that the prediction is correct with high probability. These classifiers reject test queries for which they are not sufficiently confident. The course consists of four lectures, with each lecture centered around a few recent papers but including material from other publications. I was not able to cover ALL of the relevant literature in these presentations. I would be grateful to receive email with pointers to other papers that discuss these topics. Similarly, if you see errors in these presentations, please send me email so that I can correct them.

Tom Dietterich,