Along with the text that @William proposed (it's a great reference), for bootstrapping it's hard to beat:
Efron 1987, _The Jackknife, the Bootstrap, and Other Resampling Plans_.
Efron and Tibshirani 1994, _An Introduction to the Bootstrap_.
Hall 1995, _The Bootstrap and Edgeworth Expansion_ is more rigorous than the above. Upon a cursory glance, it appears to dive pretty deep into the theoretical details of the bootstrap.
Specifically for boosting, Robert Schapire has a list of references to read found here. And for bagging, Martin Sewell has a list of references here. His site has a bunch of reference lists for a number of machine learning topics (see here).