Problem instances

These datasets are used in the computational experiments of the paper "Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions". Some of the portfolio instances were taken from Dvurechensky, Pavel, et al., "Generalized Self-Concordant Analysis of Frank-Wolfe algorithms". Others were generated with the same format and varying dimensions. Each file is in MAT format, contains a single matrix W of size d × p with d the decision dimension and p the number of periods.

The logistic regression instances were taken from the LIBSVM datasets and converted using libsvm2csv.
The first columns with non-numeric labels are not features and should be discarded, the outcome is the target column which may be encoded in different manners (-1 and 1, 1 and 2, etc).

The phase retrieval instances were generated in MAT format as described in the article, they all contain a W matrix, a y outcome vector and a theta vector which is not required. W has as many rows as the length of y and columns as the initial input vector.