diff --git a/src/core/base.rs b/src/core/base.rs
index 3eeb98e..7524fbc 100644
--- a/src/core/base.rs
+++ b/src/core/base.rs
@@ -51,7 +51,11 @@ pub trait Sample {
 
 impl Sample for f32 {
     fn sample_any(rng: &mut Rng) -> Self {
-        rng.f32()
+        // Sampling from the whole range is likely not desired. Choosing
+        // sqrt(MAX) as an arbitrary bound.
+        let max = f32::MAX.sqrt();
+        let min = -max;
+        rng.f32_range(min..=max)
     }
 
     fn sample_uniform(lower: Self, upper: Self, rng: &mut Rng) -> Self {
@@ -65,7 +69,11 @@ impl Sample for f32 {
 
 impl Sample for f64 {
     fn sample_any(rng: &mut Rng) -> Self {
-        rng.f64()
+        // Sampling from the whole range is likely not desired. Choosing
+        // cbrt(MAX) as an arbitrary bound.
+        let max = f64::MAX.cbrt();
+        let min = -max;
+        rng.f64_range(min..=max)
     }
 
     fn sample_uniform(lower: Self, upper: Self, rng: &mut Rng) -> Self {
diff --git a/src/solver/lipo.rs b/src/solver/lipo.rs
index d45de35..0c92c54 100644
--- a/src/solver/lipo.rs
+++ b/src/solver/lipo.rs
@@ -433,7 +433,10 @@ mod tests {
         let n = 2;
 
         let f = Sphere::new(n);
-        let dom = f.domain();
+        // We are going to run LIPO without any local optimization and "any
+        // potential minimizer" strategy. In such a setting, it would be
+        // impossible for LIPO to find good points in the unconstrained domain.
+        let dom = (0..n).map(|_| (-1.0, 1.0)).collect();
         let eps = convert(1e-3);
         let rng = Rng::with_seed(3);
         let mut options = LipoOptions::default();
@@ -443,7 +446,7 @@ mod tests {
 
         for x in f.initials() {
             let optimizer = Lipo::with_options(&f, &dom, options.clone(), rng.clone());
-            optimize(&f, &dom, optimizer, x, convert(0.0), 250, eps).unwrap();
+            optimize(&f, &dom, optimizer, x, convert(0.0), 1000, eps).unwrap();
         }
     }
 }