Madeleine Udell

Using 1x1 SDP variables produces some wonky behavior. The problem ``` using Convex m = 2 k = 1 AX = rand(m) AVV = rand(m, k^2) alpha = Variable() S...

Make pyjulia easy to install

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I'd like to make it easy for Python denizens to use my Julia packages, so am writing a thin Python wrapper using pyjulia. But to make my wrapper easily installable,...

Register version v1.1.1

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Register new version

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Consider using [traits](https://github.com/mauro3/Traits.jl) for losses and regularizers, in order to ensure that new losses and regularizers added implement the required methods (evaluate, grad, prox, etc). Might also be more efficient...

shsprandn and shsprand don't guarantee that entries have unique values; ie I can have an entry [3,4] = .4 and [3,5] = -.2. This is fine if I'm only multiplying...

Compute transpose in parallel

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Currently the transpose of the shared sparse matrix is computed in serial by calling transpose on a local version of the matrix: `transpose(A) = share(transpose(localize(A)))`. We should be able to...