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Split Linearized Bregman Iteration

Project description

Citing libra_py_001_05

The library libra_py is an academic project. The time and resources spent developing fastFM are therefore justified
by the number of citations of the software. If you publish scientific articles using libra_py, please cite the following article (bibtex entry 'citation.bib <>' ).

Huang, Chendi and Sun, Xinwei and Xiong, Jiechao and Yao, Yuan. "Split LBI: An Iterative Regularization Path with Structural Sparsity" Advances in Neural Information Processing Systems 29, pp. 3369--3377 (2016)

libra_py_001_05: A Package for sparsity problem

.. code-block:: python

from libra_py_001_05 import lbi
obj = lbi.LB(X,y,family='gaussian')

Tutorials and other information are available 'here <>' and
'here <>'.

The R code is available as 'subrepository <>'; the Matlab code is available as 'subrepository <>'.

If you have still **questions** after reading the documentation please open a issue at GitHub.

| Family | Solver | Loss |
| Gaussian | LBI_Linear | Square Loss |
| Binomial | LBI_Logit | Logit Model |

*Supported solvers and tasks*


**binary install**

``pip install libra_py_001_05``

import libra_py_001_05

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