Merge pull request #500 from mblondel:release-0.8

PiperOrigin-RevId: 557031423

docs/changelog.rst

@@ -1,6 +1,43 @@
 Changelog
 =========
 
+Version 0.8
+-----------
+
+New features
+~~~~~~~~~~~~
+
+- Added Broyden algorithm to solve non linear root equations, by Zaccharie Ramzi.
+
+Bug fixes and enhancements
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+- Fixed "LBFGSB produces NaN for certain conditions", by Vincent Roulet.
+- Better layout for notebook gallery, by Fabian Pedregosa.
+- Added support for complex numbers in nonlinear conjugate gradient, by Gregor Thalhammer.
+- Added support for complex numbers in LBFGS and zoom line search, by Gregor Thalhammer.
+- Various LBFGS improvements, by Vincent Roulet.
+- Completely revamped zoom linesearch, by Vincent Roulet.
+- Added continuous integration for python 3.11, fixed typing extension issue, by Vincent Roulet.
+- Added number of function/grad/prox/etc... evaluation for various solvers, by Zaccharie Ramzi.
+- Fixed implicit differentiation in LBFGSB, by Nathan Simpson.
+- Ensure weak-type consistency, by Mathieu Blondel.
+- Extend convenience API for QP + doc, by Louis Bethune.
+- Add interpolation explanations for Polyak/Armijo API doc, by Louis Bethune.
+- Support has_aux in AndersonAcceleration, by Louis Bethune.
+- Drop Python 3.7 support, by Mathieu Blondel.
+- Fixed typos in perturbation docs, by Guillaume Dalle.
+- Fixed pytree support in tree_inf_norm, by Emily Fertig.
+- Fixed NaN handling in LBFGSB, by Srinivas Vasudevan.
+- Use jnp.ndarray instead of jnp.array, by Peter Hawkins.
+
+Contributors
+~~~~~~~~~~~~
+
+Louis Bethune, Emily Fertig, Fabian Pedregosa, Gregor Thalhammer-Thurner,
+Guillaume Dalle, Mathieu Blondel, Nathan Simpson, Peter Hawkins,
+Srinivas Vasudevan, Vincent Roulet, Zaccharie Ramzi.
+
 Version 0.7
 -----------
 

docs/root_finding.rst

@@ -82,7 +82,7 @@ Broyden's method is an iterative algorithm suitable for nonlinear root equations
 It is a quasi-Newton method (like L-BFGS), meaning that it uses an approximation of the Jacobian matrix
 at each iteration.
 The approximation is updated at each iteration with a rank-one update.
-This makes the approximation easy to invert using the Sherman-Morrison formula, given it does not use too many
+This makes the approximation easy to invert using the Sherman-Morrison formula, provided that it does not use too many
 updates.
 One can control the number of updates with the ``history_size`` argument.
 Furthermore, Broyden's method uses a line search to ensure the rank-one updates are stable.

jaxopt/version.py

@@ -14,4 +14,4 @@
 
 """JAXopt version."""
 
-__version__ = "0.7"
+__version__ = "0.8"