diff --git a/Numeric/SGD/Grad.hs b/Numeric/SGD/Grad.hs
--- a/Numeric/SGD/Grad.hs
+++ b/Numeric/SGD/Grad.hs
@@ -23,10 +23,13 @@
 , parUnions
 ) where
 
-import Control.Applicative ((<$>), (<*>))
 import Data.List (foldl')
 import qualified Data.IntMap as M
+#if MIN_VERSION_containers(0,4,2)
+import Control.Applicative ((<$>), (<*>))
 import Control.Monad.Par.Scheds.Direct (Par, runPar, spawn, get)
+#else
+#endif
 
 import Numeric.SGD.LogSigned
 
diff --git a/Numeric/SGD/LogSigned.hs b/Numeric/SGD/LogSigned.hs
--- a/Numeric/SGD/LogSigned.hs
+++ b/Numeric/SGD/LogSigned.hs
@@ -14,9 +14,7 @@
 
 import qualified Data.Number.LogFloat as L
 import Data.Function (on)
-import Control.Monad.Par (NFData)
-
-instance NFData L.LogFloat
+import Control.DeepSeq (NFData(..))
 
 -- | Signed real value in the logarithmic domain.
 data LogSigned = LogSigned
@@ -31,7 +29,8 @@
     compare = compare `on` toLogFloat
 
 -- All fields are strict and unpacked.
-instance NFData LogSigned
+instance NFData LogSigned where
+    rnf (LogSigned p q) = p `seq` q `seq` ()
 
 -- | Smart LogSigned constructor.
 {-# INLINE logSigned #-}
diff --git a/sgd.cabal b/sgd.cabal
--- a/sgd.cabal
+++ b/sgd.cabal
@@ -1,5 +1,5 @@
 name:               sgd
-version:            0.2.0
+version:            0.2.1
 synopsis:           Stochastic gradient descent
 description:
     Implementation of a Stochastic Gradient Descent optimization method.
@@ -29,6 +29,7 @@
       , primitive
       , logfloat
       , monad-par
+      , deepseq
 
     exposed-modules:
         Numeric.SGD