Merge branch 'master' into dev-0.6

Author: mateuszbaran

Changelog.md

@@ -50,6 +50,24 @@ This is a breaking change since the JuMP extension is dropped.
 
 ### Changed
 
+* The default restart rule for `conjugate_gradient_descent` is now `RestartOnNonDescent` instead of `NeverRestart`, which makes the algorithm more robust to non-convexity and numerical issues. The old default can still be used by explicitly passing `restart_condition=NeverRestart()`. (#604)
+* `HagerZhangCoefficientRule` now has a safeguard against the denominator being too close to zero (the `denom_threshold` field). By default it is set to 1.0e-10. You can set it to a lower positive value (or even zero) to weaken the safeguard, but it is recommended to keep it to avoid numerical issues. (#604)
+* introduce for all `Rule`s also a variant without being encapsulated in a memory, where the old values have to be passed as keywords. This is now used by the `ConjugateGradientBealeRestartRule` when evaluating its inner rule. (#604)
+
+## [0.5.36] April 24, 2026
+
+### Added
+
+* a function `stopped_at(state)` to access the number of iterations it took a solver to stop. (#599)
+
+### Fixed
+
+* a small bug where `get_count(sc::StopWhenAny, Val(:Iteration))` wrongly reported it stopped before the first iteration when it actually did not yet stop. (#599)
+
+## [0.5.35] April 16, 2026
+
+### Changed
+
 * `NonlinearLeastSquaresObjective` is now called `ManifoldNonlinearLeastSquaresObjective` (#569).
 * This is a breaking release in order to move a few parts to a unified naming and since we
 discontinue the `JuMP` extension. (#532)

test/plans/test_conjugate_gradient_plan.jl

@@ -17,19 +17,21 @@ Manopt.update_rule_storage_vectors(::DummyCGCoeff) = Tuple{}
         p0 = [1.0, 0.0]
         pr = DefaultManoptProblem(M, ManifoldGradientObjective(f, grad_f))
         cgs2 = ConjugateGradientDescentState(
-            M;
-            p = p0, stopping_criterion = StopAfterIteration(2),
-            stepsize = Manopt.ConstantStepsize(M, 1.0), coefficient = dur2,
+            M; p = p0,
+            stopping_criterion = StopAfterIteration(2),
+            stepsize = Manopt.ConstantStepsize(M, 1.0),
+            coefficient = dur2,
         )
         cgs2.X = [0.0, 0.2]
         # Fake update history to get a certain old X and old p
         cgs2.coefficient(pr, cgs2, 0)
         # the inner check is 0.2 which is still less than 0.3
         @test cgs2.coefficient(pr, cgs2, 1) != 0
         cgs3 = ConjugateGradientDescentState(
-            M;
-            p = p0, stopping_criterion = StopAfterIteration(2),
-            stepsize = Manopt.ConstantStepsize(M, 1.0), coefficient = dur3,
+            M; p = p0,
+            stopping_criterion = StopAfterIteration(2),
+            stepsize = Manopt.ConstantStepsize(M, 1.0),
+            coefficient = dur3,
         )
         cgs3.X = [0.0, 0.2]
         # Fake update history to get a certain old X and old p