diff --git a/.travis.yml b/.travis.yml
index ffa7f08..ced673a 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -3,13 +3,13 @@ os:
   - linux
   - osx
 julia:
-  - 0.3
   - 0.4
+  - 0.5
   - nightly
 notifications:
   email: false
-script:
-  - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
-  - julia --check-bounds=yes -e 'Pkg.clone(pwd()); Pkg.build("RegERMs"); Pkg.test("RegERMs"; coverage=true)'
+# script:
+#   - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
+#   - julia --check-bounds=yes -e 'Pkg.clone(pwd()); Pkg.build("RegERMs"); Pkg.test("RegERMs"; coverage=true)'
 after_success:
   - julia -e 'cd(Pkg.dir("RegERMs")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
diff --git a/Makefile b/Makefile
deleted file mode 100644
index be02bbc..0000000
--- a/Makefile
+++ /dev/null
@@ -1,3 +0,0 @@
-.PHONY: test
-test:
-	julia ./test/runtests.jl
diff --git a/REQUIRE b/REQUIRE
index dd9971e..4051e8e 100644
--- a/REQUIRE
+++ b/REQUIRE
@@ -1,3 +1,3 @@
-julia 0.3
+julia 0.4
 StatsBase 0.6.0
 Optim 0.3.1
diff --git a/src/RegERMs.jl b/src/RegERMs.jl
index 21dc523..ad2d9bb 100644
--- a/src/RegERMs.jl
+++ b/src/RegERMs.jl
@@ -1,3 +1,5 @@
+VERSION >= v"0.4.0-dev+6521" && __precompile__()
+
 module RegERMs
 
 using StatsBase
diff --git a/src/solvers/lbfgs.jl b/src/solvers/lbfgs.jl
index 71e72d6..66b9244 100644
--- a/src/solvers/lbfgs.jl
+++ b/src/solvers/lbfgs.jl
@@ -2,24 +2,27 @@ type LBFGSSolver <: RegressionSolver end
 
 function solve(model::RegressionModel, method::RegERM, ::LBFGSSolver, X::AbstractMatrix, y::AbstractVector)
     function tloss_grad(theta::Vector)
-      n = size(X,1)
+        n = size(X,1)
 
-      grad_model = gradient(model.f, X[1,:], theta)
-      grad_loss = derivs(loss(method), values(model, X[1,:], theta), [y[1]])
+        grad_model = gradient(model.f, X[1:1,:], theta)
+        grad_loss = derivs(loss(method), values(model, X[1:1,:], theta), [y[1]])
 
-      total = broadcast(*, grad_loss',grad_model)
-      for i = 2:n
-        grad_model = gradient(model.f, X[i,:], theta)
-        grad_loss = derivs(loss(method), values(model, X[i,:], theta), [y[i]])
+        total = broadcast(*, grad_loss',grad_model)
+        for i = 2:n
+            grad_model = gradient(model.f, X[i:i,:], theta)
+            grad_loss = derivs(loss(method), values(model, X[i:i,:], theta), [y[i]])
 
-        total += broadcast(*, grad_loss',grad_model)
-      end
-      return vec(total)
+            total += broadcast(*, grad_loss', grad_model)
+        end
+        return vec(total)
     end
 
     reg_grad(theta::Vector) = gradient(regularizer(method, theta))
-    obj(theta::Vector) = tloss(loss(method), values(model, method.X, theta), method.y) + value(regularizer(method, theta))
+    obj(theta::Vector) =
+        tloss(loss(method), values(model, method.X, theta), method.y) + value(regularizer(method, theta))
     grad!(theta::Vector, storage::Vector) = storage[:] = tloss_grad(theta) + reg_grad(theta)
 
-    Optim.optimize(obj, grad!, model.theta, method=:l_bfgs, linesearch! = Optim.interpolating_linesearch!).minimum
-end
\ No newline at end of file
+    Optim.optimize(obj, grad!,
+                   model.theta,
+                   method=LBFGS(; linesearch! = Optim.interpolating_linesearch!)).minimum
+end
diff --git a/test/runtests.jl b/test/runtests.jl
index 8a7b1a8..39c74ca 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,5 +1,3 @@
-push!(LOAD_PATH, "src")
-
 using RegERMs, Base.Test
 
 
@@ -18,4 +16,4 @@ for t in tests
     test_fn = "$t.jl"
     println("* $test_fn")
     include(test_fn)
-end
\ No newline at end of file
+end