new version v0.04

Author: statmlben

README.md

@@ -2,10 +2,11 @@
 
 **ReHLine** is designed to be a computationally efficient and practically useful software package for large-scale empirical risk minimization (ERM) problems.
 
-- GitHub repo: [https://github.com/softmin/ReHLine-python](https://github.com/softmin/ReHLine-python) 
 - Documentation: [https://rehline-python.readthedocs.io](https://rehline-python.readthedocs.io)
+- Project homepage: [https://rehline.github.io](https://rehline.github.io)
+- GitHub repo: [https://github.com/softmin/ReHLine-python](https://github.com/softmin/ReHLine-python) 
 - PyPi: [https://pypi.org/project/rehline](https://pypi.org/project/rehline)
-- Open Source: [MIT license](https://opensource.org/licenses/MIT)
+<!-- - Open Source: [MIT license](https://opensource.org/licenses/MIT) -->
 - Paper: [NeurIPS | 2023](https://openreview.net/pdf?id=3pEBW2UPAD)
 
 The **ReHLine** solver has four appealing
@@ -16,6 +17,7 @@ The **ReHLine** solver has four appealing
 - The optimization algorithm has a provable linear convergence rate.
 - The per-iteration computational complexity is linear in the sample size.
 
+<!-- 
 ## 📝 Formulation
 
 **ReHLine** is designed to address the empirical regularized ReLU-ReHU minimization problem, named *ReHLine optimization*, of the following form:
@@ -38,7 +40,7 @@ $$
 
 This formulation has a wide range of applications spanning various fields, including statistics, machine learning, computational biology, and social studies. Some popular examples include SVMs with fairness constraints (FairSVM), elastic net regularized quantile regression (ElasticQR), and ridge regularized Huber minimization (RidgeHuber).
 
-![](./figs/tab.png)
+![](./figs/tab.png) -->
 
 ## ⌛ Benchmark (powered by benchopt)
 

doc/source/README.md

@@ -1,6 +1,6 @@
 [project]
 name = "rehline"
-version = "0.0.4.dev0"
+version = "0.0.4"
 description = "Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence"
 authors = [
   {name = "Ben Dai", email = "[email protected]"},

pyproject.toml

@@ -7,7 +7,7 @@
 from setuptools import setup
 from setuptools.command.build_ext import build_ext
 
-__version__ = "0.0.4.dev0"
+__version__ = "0.0.4"
 
 # The main interface is through Pybind11Extension.
 # * You can add cxx_std=11/14/17, and then build_ext can be removed.
@@ -66,7 +66,7 @@ def __str__(self) -> str:
     version=__version__,
     author=["Ben Dai", "Yixuan Qiu"],
     author_email="[email protected]",
-    url="https://github.com/softmin/ReHLine-python",
+    url="https://rehline-python.readthedocs.io/en/latest/",
     description="Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence",
     packages=["rehline"],
     # install_requires=["requests", "pybind11", "numpy", "scipy", "scikit-learn"],