Releases: softmin/ReHLine-python
Releases · softmin/ReHLine-python
Release Note for v0.0.5
What's Changed
Major Changes:
-
@yixuan Improved Building System:
- Fixed the
setup.py
script to support building on MacOS environments. - The Github Action configuration can now automatically upload wheels to PyPI on new releases.
- Fixed the
-
@keepwith Add example of Rank Regression
- Demo for using
ReHLine
solve Rank Regression
- Demo for using
-
@statmlben Tutorials for Loss and Constraints
Minor Changes:
New Contributors
Full Changelog: v0.0.4...v0.0.5
Release Note for v0.0.4
What's Changed
Major Changes:
-
@statmlben Revised Classes:
- ReHLine: This class is designed for manually setting up problems, providing users with greater flexibility and control.
- plqERM_ridge: This class focuses on solving Empirical Risk Minimization (ERM) problems, enhancing the library's capabilities in this area.
-
@statmlben Documentation Improvements:
- Extensive enhancements have been made to the documentation, ensuring clearer guidance and support for users.
Minor Changes:
- add epsilon-insensitive loss for SVR by @Aoblex in #5
- Add a linear term to rehline.cpp by @aorazalin in #4
New Contributors
- @Aoblex made their first contribution in #5
- @aorazalin made their first contribution in #4
Full Changelog: v0.0.3...v0.0.4
Release Note for v0.0.3
Version 0.03
New Features
- Wheel Package Support for Linux and Windows:
- Added pre-built wheel packages for Linux and Windows operating systems.
- This simplifies the installation process and eliminates the need for manual compilation.
Thank you @JiantingFeng for contributing the GitHub Action file.
What's Changed
- test: set random seed and add default C by @JiantingFeng in #1
- Fix Windows Build Issue by Removing poetry build Command by @JiantingFeng in #2
- Chore and CI Enhancements by @JiantingFeng in #3
New Contributors
- @JiantingFeng made their first contribution in #1
Full Changelog: v0.1...v0.0.3
Release Note for v0.0.1
We are delighted to announce a new GitHub release of "ReHLine", a dedicated solver for Regularized Composite ReLU-ReHU Loss Minimization.