Refinements in 6.1:
- The cluster parallel learning code better supports multiple simultaneous runs, and other forms of parallelism have been mostly removed. This incidentally significantly simplifies the learning core.
- The online learning algorithms are more general, with support for l1 (via a truncated gradient variant) and l2 regularization, and a generalized form of variable metric learning.
- There is a solid persistent server mode which can train online, as well as serve answers to many simultaneous queries, either in text or binary.