1. A method performed by a computing system for learning tradeoffs between discriminative power and invariance of classifiers, comprising: receiving two or more classifiers, each classifier for classifying data and having associated therewith a kernel with corresponding kernel weight, the kernel specifying an attribute for its associated classifier; and employing a learning technique to produce a combined classifier based on the two or more received classifiers by decreasing a function of the kernel weights to learn tradeoffs between discriminative power and invariance.