diff --git a/collections/_posts/2023-10-27-LUPI.md b/collections/_posts/2023-10-27-LUPI.md
index a67a5df8..da677880 100644
--- a/collections/_posts/2023-10-27-LUPI.md
+++ b/collections/_posts/2023-10-27-LUPI.md
@@ -43,7 +43,7 @@ They apply this paradigm to SVM, the goal is to show that the convergence rate i
 
 Some propositions are demonstrated introducing oracle SVM.
 
-> Proposition 1: If any vector $$x \in X$$ belongs to one and only one of the classes and there exists an Oracle function with respect to the best decision rule in the admissible set of hyperparameters, then with the probablity $$-\eta$$ the following bound holds true
+> Proposition 1: If any vector $$x \in X$$ belongs to one and only one of the classes and there exists an Oracle function with respect to the best decision rule in the admissible set of hyperparameters, then with the probability $$-\eta$$ the following bound holds true
 > 
 > $$ P(y[(w_l,x)+b_l]<0) \leq P(1-\xi^0 <0) + A \frac{h ln\frac{l}{h}-ln (\eta)}{l}$$
 >