diff --git a/src/learner/evaluation-inl.hpp b/src/learner/evaluation-inl.hpp
index ab68a6ec6..8e63e83ec 100644
--- a/src/learner/evaluation-inl.hpp
+++ b/src/learner/evaluation-inl.hpp
@@ -83,7 +83,15 @@ struct EvalLogLoss : public EvalEWiseBase<EvalLogLoss> {
     return "logloss";
   }
   inline static float EvalRow(float y, float py) {
-    return - y * std::log(py) - (1.0f - y) * std::log(1 - py);
+    const float eps = 1e-16f;
+    const float pneg = 1.0f - py;
+    if (py < eps) {
+      return -y * std::log(eps) - (1.0f - y)  * std::log(1.0f - eps); 
+    } else if (pneg < eps) {
+      return -y * std::log(1.0f - eps) - (1.0f - y)  * std::log(eps); 
+    } else {
+      return -y * std::log(py) - (1.0f - y) * std::log(pneg);
+    }
   }
 };
 
diff --git a/src/learner/helper_utils.h b/src/learner/helper_utils.h
index ac1ec745e..d318cf8bd 100644
--- a/src/learner/helper_utils.h
+++ b/src/learner/helper_utils.h
@@ -43,6 +43,26 @@ inline static int FindMaxIndex(const std::vector<float>& rec) {
   return FindMaxIndex(BeginPtr(rec), rec.size());
 }
 
+// perform numerical safe logsum
+inline float LogSum(float x, float y) {
+  if (x < y) {
+    return y + std::log(std::exp(x - y) + 1.0f);
+  } else {
+    return x + std::log(std::exp(y - x) + 1.0f);
+  }
+}
+// numerical safe logsum
+inline float LogSum(const float *rec, size_t size) {
+  float mx = rec[0];
+  for (size_t i = 1; i < size; ++i) {
+    mx = std::max(mx, rec[i]);
+  }
+  float sum = 0.0f;
+  for (size_t i = 0; i < size; ++i) {
+    sum += std::exp(rec[i] - mx);
+  }
+  return mx + std::log(sum);  
+}
 
 inline static bool CmpFirst(const std::pair<float, unsigned> &a,
                             const std::pair<float, unsigned> &b) {
diff --git a/src/utils/quantile.h b/src/utils/quantile.h
index fe8589ad8..47ada7210 100644
--- a/src/utils/quantile.h
+++ b/src/utils/quantile.h
@@ -297,6 +297,14 @@ struct WXQSummary : public WQSummary<DType, RType> {
     RType begin = src.data[0].rmax;
     size_t n = maxsize - 1, nbig = 0;
     const RType range = src.data[src.size - 1].rmin - begin;
+    // prune off zero weights 
+    if (range == 0) {
+      // special case, contain only two effective data pts
+      this->data[0] = src.data[0];
+      this->data[1] = src.data[src.size - 1];
+      this->size = 2;
+      return;
+    }
     const RType chunk = 2 * range / n;
     // minimized range
     RType mrange = 0;
@@ -323,9 +331,9 @@ struct WXQSummary : public WQSummary<DType, RType> {
               src.size, maxsize, static_cast<double>(range),
               static_cast<double>(chunk));      
       for (size_t i = 0; i < src.size; ++i) {
-        printf("[%lu] rmin=%g, rmax=%g, wmin=%g, isbig=%d\n", i,
-               src.data[i].rmin, src.data[i].rmax, src.data[i].wmin,
-               CheckLarge(src.data[i], chunk));
+        printf("[%lu] rmin=%g, rmax=%g, wmin=%g, v=%g, isbig=%d\n", i,
+               src.data[i].rmin, src.data[i].rmax,  src.data[i].wmin,
+               src.data[i].value, CheckLarge(src.data[i], chunk));
       }
       utils::Assert(nbig < n - 1, "quantile: too many large chunk");
     }
@@ -631,6 +639,7 @@ class QuantileSketchTemplate {
    * \param x the elemented added to the sketch
    */
   inline void Push(DType x, RType w = 1) {
+    if (w == static_cast<RType>(0)) return;
     if (inqueue.qtail == inqueue.queue.size()) {
       // jump from lazy one value to limit_size * 2
       if (inqueue.queue.size() == 1) {