diff --git a/optimization.cabal b/optimization.cabal
--- a/optimization.cabal
+++ b/optimization.cabal
@@ -1,6 +1,6 @@
 name:          optimization
 category:      Math
-version:       0.1.2
+version:       0.1.3
 license:       BSD3
 cabal-version: >= 1.10
 license-file:  LICENSE
diff --git a/src/Optimization/LineSearch.hs b/src/Optimization/LineSearch.hs
--- a/src/Optimization/LineSearch.hs
+++ b/src/Optimization/LineSearch.hs
@@ -60,6 +60,7 @@
        -> Bool         -- ^ is Armijo condition satisfied?
 armijo c1 f df x p a =
     f (x ^+^ a *^ p) <= f x + c1 * a * (df x `dot` p)
+{-# INLINE armijo #-}
 
 -- | Curvature condition
 curvature :: (Num a, Ord a, Additive f, Metric f)
@@ -71,6 +72,7 @@
           -> Bool          -- ^ is curvature condition satisfied
 curvature c2 df x p a =
     df (x ^+^ a *^ p) `dot` p >= c2 * (df x `dot` p)
+{-# INLINE curvature #-}
 
 -- | Backtracking line search algorithm
 --
diff --git a/src/Optimization/LineSearch/BFGS.hs b/src/Optimization/LineSearch/BFGS.hs
--- a/src/Optimization/LineSearch/BFGS.hs
+++ b/src/Optimization/LineSearch/BFGS.hs
@@ -11,13 +11,12 @@
 import Optimization.LineSearch
 import Control.Applicative
 import Data.Traversable
-import Data.Distributive
 import Data.Foldable
 
 -- | Broyden–Fletcher–Goldfarb–Shanno (BFGS) method
 -- @bfgs search df b0 x0@ where @b0@ is the inverse Hessian (the
 -- identity is often a good initial value).
-bfgs :: ( Metric f, Additive f, Distributive f, Foldable f, Traversable f, Applicative f
+bfgs :: ( Metric f, Additive f, Foldable f, Traversable f, Applicative f
         , Fractional a, Epsilon a)
      => LineSearch f a   -- ^ line search method
      -> (f a -> f a)     -- ^ gradient of function