[DOC] polish details

docs/components/learnware.rst

@@ -137,4 +137,4 @@ on ``user_data``.
 References
 -----------
 
-.. [1] Yu-Chang Wu, Yi-Xiao He, Chao Qian, and Zhi-Hua Zhou. Multi-objective evolutionary ensemble pruning guided by margin distribution. In *Proceedings of the 17th International Conference on Parallel Problem Solving from Nature*, 2022.
+.. [1] Yu-Chang Wu, Yi-Xiao He, Chao Qian, and Zhi-Hua Zhou. Multi-objective evolutionary ensemble pruning guided by margin distribution. In: *Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22)*, 2022, pp.427-441.

docs/components/market.rst

@@ -56,7 +56,7 @@ They share the same ``checker`` module and have different implementations of ``o
 Easy Market
 -------------
 
-Easy market is a basic realization of the learnware doc system. It consists of ``EasyOrganizer``, ``EasySearcher``, and the checker list ``[EasySemanticChecker, EasyStatChecker]``.
+Easy market is a basic realization of the learnware market. It consists of ``EasyOrganizer``, ``EasySearcher``, and the checker list ``[EasySemanticChecker, EasyStatChecker]``.
 
 
 ``Easy Organizer``

docs/components/spec.rst

@@ -137,4 +137,4 @@ Please refer to `COMPONENTS: Hetero Market  <../components/market.html#hetero-ma
 References
 -----------
 
-.. [1] Adrià Garriga-Alonso, Laurence Aitchison, and Carl Edward Rasmussen. Deep convolutional networks as shallow gaussian processes. In *International Conference on Learning Representations*, 2019.
+.. [1] Adrià Garriga-Alonso, Laurence Aitchison, and Carl Edward Rasmussen. Deep convolutional networks as shallow gaussian processes. In: *International Conference on Learning Representations (ICLR'19)*, 2019.

learnware/reuse/ensemble_pruning.py

@@ -15,7 +15,7 @@ class EnsemblePruningReuser(BaseReuser):
     """
     Baseline Multiple Learnware Reuser uing Marign Distribution guided multi-objective evolutionary Ensemble Pruning (MDEP) Method.
 
-    References: [1] Yu-Chang Wu, Yi-Xiao He, Chao Qian, and Zhi-Hua Zhou. Multi-objective Evolutionary Ensemble Pruning Guided by Margin Distribution. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), Dortmund, Germany, 2022.
+    References: [1] Yu-Chang Wu, Yi-Xiao He, Chao Qian, and Zhi-Hua Zhou. Multi-objective evolutionary ensemble pruning guided by margin distribution. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), 2022, pp.427-441.
     """
 
     def __init__(self, learnware_list: List[Learnware] = None, mode: str = "classification"):

learnware/specification/regular/image/cnn_gp.py

@@ -11,7 +11,7 @@ With this package, we are able to accurately and efficiently compute the kernel
 
 Github Repository: https://github.com/cambridge-mlg/cnn-gp
 
-References: [1] A. Garriga-Alonso, L. Aitchison, and C. E. Rasmussen. Deep Convolutional Networks as shallow Gaussian Processes. In: International Conference on Learning Representations (ICLR'19), 2019.
+References: [1] Adrià Garriga-Alonso, Laurence Aitchison, and Carl Edward Rasmussen. Deep convolutional networks as shallow gaussian processes. In: International Conference on Learning Representations (ICLR'19), 2019.
 """