  Machine learning methods have had spectacular success on numerous problems.
Here we show that a prominent class of learning algorithms - including Support
Vector Machines (SVMs) -- have a natural interpretation in terms of ecological
dynamics. We use these ideas to design new online SVM algorithms that exploit
ecological invasions, and benchmark performance using the MNIST dataset. Our
work provides a new ecological lens through which we can view statistical
learning and opens the possibility of designing ecosystems for machine
learning.
  Supplemental code is found at https://github.com/owenhowell20/EcoSVM.
