  Modern machine learning tools offer exciting possibilities to qualitatively
change the paradigm for new particle searches. In particular, new methods can
broaden the search program by gaining sensitivity to unforeseen scenarios by
learning directly from data. There has been a significant growth in new ideas
and they are just starting to be applied to experimental data. This chapter
introduces these new anomaly detection methods, which range from fully
supervised algorithms to unsupervised, and include weakly supervised methods.
