Update cmaes.py

pypop7/optimizers/es/cmaes.py

@@ -6,16 +6,17 @@
 class CMAES(ES):
     """Covariance Matrix Adaptation Evolution Strategy (CMAES).
 
-    .. note:: `CMAES` is widely recognized as one of **State-Of-The-Art (SOTA)** evolutionary algorithms for continuous
-       black-box optimization (BBO), according to one well-recognized `Nature <https://doi.org/10.1038/nature14544>`_
-       review of Evolutionary Computation (EC).
+    .. note:: `CMAES` is widely recognized as one of **State-Of-The-Art (SOTA)** evolutionary algorithms
+       for continuous black-box optimization (BBO), according to the well-recognized `Nature
+       <https://doi.org/10.1038/nature14544>`_ review of **Evolutionary Computation**.
 
        For some (rather all) interesting applications of `CMA-ES`, please refer to e.g.,
        `[SIMULIA > CST Studio Suite > Automatic Optimization (Dassault Systèmes)]
        <https://www.3ds.com/products/simulia/cst-studio-suite/automatic-optimization>`_,
-       `[Zhang et al., 2024, PNAS]
-       <https://doi.org/10.1073/pnas.2318641121>`_, `[Longobardo et al., 2024, AIAAJ]
-       <https://arc.aiaa.org/doi/full/10.2514/1.J063251>`_, `[Wang et al., 2024, ICLR]
+       `[PNAS 2024] <https://doi.org/10.1073/pnas.2318641121>`_, `[Longobardo et al., 2024, AIAAJ]
+       <https://arc.aiaa.org/doi/full/10.2514/1.J063251>`_,
+       `[NeurIPS 2024 Spotlight] <https://openreview.net/forum?id=79q206xswc>`_,
+       `[Wang et al., 2024, ICLR]
        <https://arxiv.org/abs/2404.00451>`_, `[Gil-Fuster et al., 2024, Nature Communications]
        <https://www.nature.com/articles/s41467-024-45882-z>`_, `[Jin et al., 2024]
        <https://link.springer.com/article/10.1007/s11044-024-09982-4>`_, `[Koginov et al., 2024, TMRB]