Closed riedelcastro closed 9 years ago
Do you think our Tensor data structure and it's sampling mechanisms should go in there as well?
I am wondering if it could be a simpler, possibly immutable representation of the tensor, to keep the complexity of this low.
Done with an initial version of it... can be made prettier though. Next, use this for a spec that fails once MF doesn't work anymore.
Cool! Looks nice, we can iterate on this. One step could be to get rid of the var thetaStar, and use the style of the linear classifier where theta star is mixed in, either learned, or loaded. The other step is replacing the Predictor logic with the fun(...) method as used in the other examples.
On Sat, Mar 28, 2015 at 6:04 PM, Tim Rocktäschel notifications@github.com wrote:
Done with an initial version of it... can be made prettier though. Next, use this for a spec that fails once MF doesn't work anymore.
— Reply to this email directly or view it on GitHub https://github.com/wolfe-pack/wolfe/issues/140#issuecomment-87274707.
In the spirit of the linear classifier and linear chain interfaces, which hide some of the Wolfe term and domain internals, it would be good to have a similar thing for matrix factorization.