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.

中文翻译：

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机器学习作为生态学

机器学习方法在许多问题上取得了巨大的成功。在这里，我们展示了一类著名的学习算法——包括支持向量机（SVM）——在生态动力学方面具有自然的解释。我们利用这些想法来设计新的在线 SVM 算法，利用生态入侵，并使用 MNIST 数据集进行性能基准测试。我们的工作提供了一个新的生态视角，通过它我们可以观察统计学习，并开启了设计机器学习生态系统的可能性。