From 79605eb9897d694079c0942c12bf365ef8a61b87 Mon Sep 17 00:00:00 2001
From: Joerg Kappes <kappes@math.uni-heidelberg.de>
Date: Thu, 16 Jul 2015 09:53:41 +0200
Subject: [PATCH 01/19] Update lweightedsum_of_functions.hxx

fix typo in assert-loop
---
 .../opengm/functions/learnable/lweightedsum_of_functions.hxx    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
index f831329..7180164 100644
--- a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
+++ b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
@@ -77,7 +77,7 @@ LWeightedSumOfFunctions<T, I, L>::LWeightedSumOfFunctions
    :   shape_(shape), weights_(&weights), weightIDs_(weightIDs),feat_(feat)
 {
    OPENGM_ASSERT( weightIDs_.size() == feat_.size() );
-   for(size_t i=0 i<weightIDs_.size();++1)
+   for(size_t i=0; i<weightIDs_.size(); ++i)
       OPENGM_ASSERT( size() == feat_[i].size() );
 }
 

From df112955a5055f71d85f01db024a4d382f39f3df Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Tue, 15 Sep 2015 15:11:00 +0200
Subject: [PATCH 02/19] RebindGm added to LPCplex2

---
 include/opengm/inference/lpcplex.hxx          | 15 ++++++++-------
 include/opengm/inference/lpcplex2.hxx         |  9 +++++++++
 include/opengm/learning/bundle-optimizer.hxx  |  2 +-
 include/opengm/learning/solver/CplexBackend.h |  1 -
 src/unittest/test_gm_learning_functions.cxx   |  4 ++--
 5 files changed, 20 insertions(+), 11 deletions(-)

diff --git a/include/opengm/inference/lpcplex.hxx b/include/opengm/inference/lpcplex.hxx
index 52712c8..07c77f4 100644
--- a/include/opengm/inference/lpcplex.hxx
+++ b/include/opengm/inference/lpcplex.hxx
@@ -482,7 +482,7 @@ LPCplex<GM, ACC>::infer
          break; 
       }
 
-      // MIP EMPHASIS 
+      // MIP EMPHASIS
       switch(parameter_.mipEmphasis_) {
       case MIP_EMPHASIS_BALANCED:
          cplex_.setParam(IloCplex::MIPEmphasis, 0);
@@ -503,11 +503,11 @@ LPCplex<GM, ACC>::infer
 
       // verbose options
       if(parameter_.verbose_ == false) {
-	cplex_.setParam(IloCplex::MIPDisplay, 0);
-        cplex_.setParam(IloCplex::BarDisplay, 0);
-	cplex_.setParam(IloCplex::SimDisplay, 0);
-        cplex_.setParam(IloCplex::NetDisplay, 0);
-	cplex_.setParam(IloCplex::SiftDisplay, 0);
+       cplex_.setParam(IloCplex::MIPDisplay, 0);
+       cplex_.setParam(IloCplex::BarDisplay, 0);
+       cplex_.setParam(IloCplex::SimDisplay, 0);
+       cplex_.setParam(IloCplex::NetDisplay, 0);
+       cplex_.setParam(IloCplex::SiftDisplay, 0);
       } 
          
       // tolarance settings
@@ -555,11 +555,12 @@ LPCplex<GM, ACC>::infer
       //cplex_.setParam(IloCplex::MIRCuts, parameter_.MIRCutLevel_);
   
       // solve problem
+
       if(!cplex_.solve()) {
          std::cout << "failed to optimize. " <<cplex_.getStatus() << std::endl;
          return UNKNOWN;
       } 
-      cplex_.getValues(sol_, x_);  
+      cplex_.getValues(sol_, x_);
    }
    catch(IloCplex::Exception e) {
       std::cout << "caught CPLEX exception: " << e << std::endl;
diff --git a/include/opengm/inference/lpcplex2.hxx b/include/opengm/inference/lpcplex2.hxx
index 8769055..6ed2d88 100644
--- a/include/opengm/inference/lpcplex2.hxx
+++ b/include/opengm/inference/lpcplex2.hxx
@@ -25,6 +25,15 @@ public:
 
    // public member functions
    virtual std::string name() const;
+   template<class _GM>
+   struct RebindGm{
+       typedef LPCplex2<_GM, ACC_TYPE> type;
+   };
+
+   template<class _GM,class _ACC>
+   struct RebindGmAndAcc{
+       typedef LPCplex2<_GM, _ACC > type;
+   };
 };
 
 template<class GM_TYPE, class ACC_TYPE>
diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index 7b020c6..aebe248 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -161,7 +161,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
         Weights w_tm1 = w;
 
-		//std::cout << "current w is " << w_tm1 << std::endl;
+        //std::cout << "current w is " << w_tm1 << std::endl;
 
 		// value of L at current w
 		T L_w_tm1 = 0.0;
diff --git a/include/opengm/learning/solver/CplexBackend.h b/include/opengm/learning/solver/CplexBackend.h
index d330917..b4819e5 100644
--- a/include/opengm/learning/solver/CplexBackend.h
+++ b/include/opengm/learning/solver/CplexBackend.h
@@ -330,7 +330,6 @@ CplexBackend::solve(Solution& x, double& value, std::string& msg) {
             std::cerr << "Invalid value for MIP focus!" << std::endl;
 
         setNumThreads(_parameter.numThreads);
-
         if(!cplex_.solve()) {
            std::cout << "failed to optimize. " << cplex_.getStatus() << std::endl;
            msg = "Optimal solution *NOT* found";
diff --git a/src/unittest/test_gm_learning_functions.cxx b/src/unittest/test_gm_learning_functions.cxx
index 653e0d6..b797175 100644
--- a/src/unittest/test_gm_learning_functions.cxx
+++ b/src/unittest/test_gm_learning_functions.cxx
@@ -40,8 +40,8 @@ struct GraphicalModelTest {
       ValueType, //value type (should be float double or long double)
       opengm::Multiplier, //operator (something like Adder or Multiplier)
       typename opengm::meta::TypeListGenerator<
-         opengm::ExplicitFunction<ValueType,I,L>, 
-         opengm::PottsNFunction<ValueType,I,L> 
+         opengm::ExplicitFunction<ValueType,I,L>,
+         opengm::PottsNFunction<ValueType,I,L>
       >::type, //implicit function functor
       opengm::DiscreteSpace<I, L>
    >  GraphicalModelType;

From 043e99a3766e4dd2e0af30e9f45dec7ef6cd47df Mon Sep 17 00:00:00 2001
From: Carsten Haubold <carstenhaubold@googlemail.com>
Date: Fri, 18 Sep 2015 16:19:45 +0200
Subject: [PATCH 03/19] Add RebindGM to LPCplex2 so that it can be used for
 structured learning

---
 include/opengm/inference/lpcplex2.hxx | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/include/opengm/inference/lpcplex2.hxx b/include/opengm/inference/lpcplex2.hxx
index 8769055..b2a5d20 100644
--- a/include/opengm/inference/lpcplex2.hxx
+++ b/include/opengm/inference/lpcplex2.hxx
@@ -25,6 +25,16 @@ public:
 
    // public member functions
    virtual std::string name() const;
+
+   template<class _GM>
+   struct RebindGm{
+       typedef LPCplex2<_GM, ACC_TYPE> type;
+   };
+
+   template<class _GM,class _ACC>
+   struct RebindGmAndAcc{
+       typedef LPCplex2<_GM, _ACC > type;
+   };
 };
 
 template<class GM_TYPE, class ACC_TYPE>

From c7cbe6cb368133cc8c91cf5b572eca85163fe3f5 Mon Sep 17 00:00:00 2001
From: Carsten Haubold <carstenhaubold@googlemail.com>
Date: Fri, 18 Sep 2015 17:29:15 +0200
Subject: [PATCH 04/19] Fix an #elif statement to find the cplex backend for
 the struct-max-margin solver

---
 include/opengm/learning/solver/QuadraticSolverFactory.h | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/opengm/learning/solver/QuadraticSolverFactory.h b/include/opengm/learning/solver/QuadraticSolverFactory.h
index 43ca5bc..e986630 100644
--- a/include/opengm/learning/solver/QuadraticSolverFactory.h
+++ b/include/opengm/learning/solver/QuadraticSolverFactory.h
@@ -3,7 +3,7 @@
 
 #ifdef WITH_GUROBI
 #include "GurobiBackend.h"
-#elif WITH_CPLEX
+#elif defined(WITH_CPLEX)
 #include "CplexBackend.h"
 #endif
 
@@ -19,7 +19,7 @@ class QuadraticSolverFactory {
 
 #ifdef WITH_GUROBI
 	return new GurobiBackend();
-#elif WITH_CPLEX
+#elif defined(WITH_CPLEX)
         return new CplexBackend();
 #endif
 

From 6f4c40805d007c8b336c29cdaa001f9a98be4884 Mon Sep 17 00:00:00 2001
From: Carsten Haubold <carstenhaubold@googlemail.com>
Date: Fri, 25 Sep 2015 21:03:21 +0200
Subject: [PATCH 05/19] Add LpGurobi2::RebindGm to allow learning with Gurobi
 solver

---
 include/opengm/inference/lpgurobi2.hxx | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/include/opengm/inference/lpgurobi2.hxx b/include/opengm/inference/lpgurobi2.hxx
index a9c1a9c..192b038 100644
--- a/include/opengm/inference/lpgurobi2.hxx
+++ b/include/opengm/inference/lpgurobi2.hxx
@@ -25,6 +25,16 @@ public:
 
    // public member functions
    virtual std::string name() const;
+
+   template<class _GM>
+   struct RebindGm{
+       typedef LPGurobi2<_GM, ACC_TYPE> type;
+   };
+
+   template<class _GM,class _ACC>
+   struct RebindGmAndAcc{
+       typedef LPGurobi2<_GM, _ACC > type;
+   };
 };
 
 template<class GM_TYPE, class ACC_TYPE>

From c8990ba17fe8f98cca5e4e096ecd4bf48e6361d4 Mon Sep 17 00:00:00 2001
From: Carsten Haubold <carstenhaubold@googlemail.com>
Date: Wed, 7 Oct 2015 15:31:43 +0200
Subject: [PATCH 06/19] Use IndexType instead of UInt16 in LearnableUnary, to
 allow large numbers of features

---
 include/opengm/functions/learnable/lunary.hxx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/opengm/functions/learnable/lunary.hxx b/include/opengm/functions/learnable/lunary.hxx
index c4cc08a..cc1b930 100644
--- a/include/opengm/functions/learnable/lunary.hxx
+++ b/include/opengm/functions/learnable/lunary.hxx
@@ -101,8 +101,8 @@ protected:
 
     mutable const opengm::learning::Weights<T> *    weights_;
 
-    opengm::UInt16Type numberOfLabels_;
-    std::vector<opengm::UInt16Type> offsets_;
+    IndexType numberOfLabels_;
+    std::vector<IndexType> offsets_;
     std::vector<size_t> weightIds_;
     std::vector<ValueType> features_;
 

From b46caa64078682222cb2a06e28aea4e6c29ca599 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Thu, 15 Oct 2015 20:15:53 +0200
Subject: [PATCH 07/19] lweighted sum of functions calls operator() on Marray
 with proper indices for dimension =2 (and 1)

---
 .../functions/learnable/lweightedsum_of_functions.hxx  | 10 +++++++++-
 include/opengm/learning/bundle-optimizer.hxx           |  8 ++++----
 2 files changed, 13 insertions(+), 5 deletions(-)

diff --git a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
index 7180164..eaa7d28 100644
--- a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
+++ b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
@@ -99,7 +99,15 @@ LWeightedSumOfFunctions<T, I, L>::weightGradient
    ITERATOR begin
 ) const {
   OPENGM_ASSERT(weightNumber< numberOfWeights());
-  return feat_[weightNumber](*begin);
+
+  if(dimension()==1){
+    return feat_[weightNumber](*begin);
+  }
+  else if(dimension()==2){
+    return feat_[weightNumber](*begin, *(begin+1));
+  }
+  else
+    OPENGM_ASSERT(dimension()<=2);
 }
 
 template <class T, class I, class L>
diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index aebe248..1135b0b 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -157,7 +157,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
 		t++;
 
-		std::cout << std::endl << "----------------- iteration " << t << std::endl;
+        std::cout << std::endl << "----------------- iteration " << t << std::endl;
 
         Weights w_tm1 = w;
 
@@ -173,7 +173,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		oracle(w_tm1, L_w_tm1, a_t);
 
 		std::cout << "       L(w)              is: " << L_w_tm1 << std::endl;
-		//std::cout << "      ∂L(w)/∂            is: " << a_t << std::endl;
+        //std::cout << "      ∂L(w)/∂            is: " << a_t << std::endl;
 
 		// update smallest observed value of regularized L
 		minValue = std::min(minValue, L_w_tm1 + _parameter.lambda*0.5*dot(w_tm1, w_tm1));
@@ -183,7 +183,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		// compute hyperplane offset
 		T b_t = L_w_tm1 - dot(w_tm1, a_t);
 
-		//std::cout << "adding hyperplane " << a_t << "*w + " << b_t << std::endl;
+        //std::cout << "adding hyperplane " << a_t << "*w + " << b_t << std::endl;
 
 		// update lower bound
 		_bundleCollector.addHyperplane(a_t, b_t);
@@ -195,7 +195,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		findMinLowerBound(w, minLower);
 
 		std::cout << " min_w ℒ(w)   + ½λ|w|²   is: " << minLower << std::endl;
-		//std::cout << " w* of ℒ(w)   + ½λ|w|²   is: "  << w << std::endl;
+        //std::cout << " w* of ℒ(w)   + ½λ|w|²   is: "  << w << std::endl;
 
 		// compute gap
 		T eps_t;

From db4e221c20b4733eaa32246ef31c95e7e5105884 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Wed, 21 Oct 2015 14:53:47 +0200
Subject: [PATCH 08/19] corrects indexing call from a learnable
 function.weightGradient to a multidimensional marray (*begin ---> begin)
 (this was working correctly only for 1-dim marrays)

---
 .../opengm/datastructures/marray/marray.hxx   |  1 +
 .../learnable/lweightedsum_of_functions.hxx   | 12 ++-----
 .../opengm/inference/lp_inference_base.hxx    |  1 -
 include/opengm/learning/bundle-optimizer.hxx  | 31 +++++++++++++++----
 .../opengm/learning/gradient-accumulator.hxx  |  3 --
 5 files changed, 29 insertions(+), 19 deletions(-)

diff --git a/include/opengm/datastructures/marray/marray.hxx b/include/opengm/datastructures/marray/marray.hxx
index 0c91d2f..7871e7e 100644
--- a/include/opengm/datastructures/marray/marray.hxx
+++ b/include/opengm/datastructures/marray/marray.hxx
@@ -15,6 +15,7 @@
 #include <iostream> // cout
 #include <memory> // allocator
 #include <numeric> // accumulate
+#include <typeinfo>
 
 /// Runtime-flexible multi-dimensional views and arrays
 namespace marray {
diff --git a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
index eaa7d28..5978c52 100644
--- a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
+++ b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
@@ -79,6 +79,8 @@ LWeightedSumOfFunctions<T, I, L>::LWeightedSumOfFunctions
    OPENGM_ASSERT( weightIDs_.size() == feat_.size() );
    for(size_t i=0; i<weightIDs_.size(); ++i)
       OPENGM_ASSERT( size() == feat_[i].size() );
+      for(size_t j=0; j<dimension(); ++j)
+          OPENGM_ASSERT( shape(j) == feat_[i].shape(j))
 }
 
 template <class T, class I, class L>
@@ -99,15 +101,7 @@ LWeightedSumOfFunctions<T, I, L>::weightGradient
    ITERATOR begin
 ) const {
   OPENGM_ASSERT(weightNumber< numberOfWeights());
-
-  if(dimension()==1){
-    return feat_[weightNumber](*begin);
-  }
-  else if(dimension()==2){
-    return feat_[weightNumber](*begin, *(begin+1));
-  }
-  else
-    OPENGM_ASSERT(dimension()<=2);
+  return feat_[weightNumber](begin);
 }
 
 template <class T, class I, class L>
diff --git a/include/opengm/inference/lp_inference_base.hxx b/include/opengm/inference/lp_inference_base.hxx
index 36fc750..cf47706 100644
--- a/include/opengm/inference/lp_inference_base.hxx
+++ b/include/opengm/inference/lp_inference_base.hxx
@@ -1842,7 +1842,6 @@ inline LPInferenceBase<LP_INFERENCE_TYPE>::LPInferenceBase(const GraphicalModelT
    if(!opengm::meta::Compare<OperatorType, opengm::Adder>::value) {
       throw RuntimeError("This implementation does only supports Min-Sum-Semiring and Max-Sum-Semiring.");
    }
-
    // sort factors
    sortFactors();
 
diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index 1135b0b..7f99d5d 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -153,7 +153,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
 	unsigned int t = 0;
 
-	while (true) {
+    while (true) {
 
 		t++;
 
@@ -161,7 +161,10 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
         Weights w_tm1 = w;
 
-        //std::cout << "current w is " << w_tm1 << std::endl;
+        std::cout << "w: ";
+        for(size_t i=0; i<w_tm1.size(); ++i)
+            std::cout << w_tm1[i] << " ";
+        std::cout << std::endl;
 
 		// value of L at current w
 		T L_w_tm1 = 0.0;
@@ -173,7 +176,10 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		oracle(w_tm1, L_w_tm1, a_t);
 
 		std::cout << "       L(w)              is: " << L_w_tm1 << std::endl;
-        //std::cout << "      ∂L(w)/∂            is: " << a_t << std::endl;
+        std::cout << "∂L(w)/∂:  (";
+        for(size_t i=0; i<a_t.size(); ++i)
+            std::cout << a_t[i] << " ";
+        std::cout << ")" << std::endl;
 
 		// update smallest observed value of regularized L
 		minValue = std::min(minValue, L_w_tm1 + _parameter.lambda*0.5*dot(w_tm1, w_tm1));
@@ -183,7 +189,10 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		// compute hyperplane offset
 		T b_t = L_w_tm1 - dot(w_tm1, a_t);
 
-        //std::cout << "adding hyperplane " << a_t << "*w + " << b_t << std::endl;
+        std::cout << "adding hyperplane: ( ";
+        for(size_t i=0; i<a_t.size(); ++i)
+            std::cout << a_t[i] << " ";
+        std::cout << ")*w + " << b_t << std::endl;
 
 		// update lower bound
 		_bundleCollector.addHyperplane(a_t, b_t);
@@ -191,11 +200,19 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		// minimal value of lower bound
 		T minLower;
 
-		// update w and get minimal value
+        std::cout << "w before findMinLowerBound: ";
+        for(size_t i=0; i<w.size(); ++i)
+            std::cout << w[i] << " ";
+        std::cout << std::endl;
+
+        // update w and get minimal value
 		findMinLowerBound(w, minLower);
 
 		std::cout << " min_w ℒ(w)   + ½λ|w|²   is: " << minLower << std::endl;
-        //std::cout << " w* of ℒ(w)   + ½λ|w|²   is: "  << w << std::endl;
+        std::cout << " w* of ℒ(w)   + ½λ|w|²   is: (";
+        for(size_t i=0; i<w.size(); ++i)
+            std::cout << w[i] << " ";
+        std::cout << ")" << std::endl;
 
 		// compute gap
 		T eps_t;
@@ -269,6 +286,8 @@ BundleOptimizer<T>::findMinLowerBound(ModelWeights& w, T& value) {
 
 	for (size_t i = 0; i < w.numberOfWeights(); i++)
 		w[i] = x[i];
+    for (size_t i = 0; i < w.numberOfWeights(); i++)
+        std::cout << "x[" << i << "]=" << x[i] << std::endl;
 }
 
 template <typename T>
diff --git a/include/opengm/learning/gradient-accumulator.hxx b/include/opengm/learning/gradient-accumulator.hxx
index f605122..43c9cf8 100644
--- a/include/opengm/learning/gradient-accumulator.hxx
+++ b/include/opengm/learning/gradient-accumulator.hxx
@@ -53,9 +53,7 @@ public:
         for (int i = 0; i < function.numberOfWeights(); i++) {
 
             int index = function.weightIndex(i);
-
             double g = function.weightGradient(i, Iter(accessor, 0));
-
             if (_mode == Add)
                 _gradient[index] += g;
             else
@@ -117,7 +115,6 @@ struct FeatureAccumulator{
         typedef opengm::SubsetAccessor<Iter, LABEL_ITER> Accessor;
         typedef opengm::AccessorIterator<Accessor, true> AccessorIter;
 
-
         // get the number of weights_
         const size_t nWeights = f.numberOfWeights();
         if(nWeights>0){

From 695964c3cfce7bb2ad06ba241085a2685af9f238 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Sat, 24 Oct 2015 19:30:26 +0200
Subject: [PATCH 09/19] add model print out in struct-max-margin iteration

---
 include/opengm/learning/bundle-optimizer.hxx  |  4 +---
 include/opengm/learning/struct-max-margin.hxx | 19 ++++++++++---------
 2 files changed, 11 insertions(+), 12 deletions(-)

diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index 7f99d5d..4be57e8 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -157,7 +157,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
 		t++;
 
-        std::cout << std::endl << "----------------- iteration " << t << std::endl;
+        std::cout << std::endl << "-----------------------------------------------------------------------------> iteration      " << t << std::endl;
 
         Weights w_tm1 = w;
 
@@ -286,8 +286,6 @@ BundleOptimizer<T>::findMinLowerBound(ModelWeights& w, T& value) {
 
 	for (size_t i = 0; i < w.numberOfWeights(); i++)
 		w[i] = x[i];
-    for (size_t i = 0; i < w.numberOfWeights(); i++)
-        std::cout << "x[" << i << "]=" << x[i] << std::endl;
 }
 
 template <typename T>
diff --git a/include/opengm/learning/struct-max-margin.hxx b/include/opengm/learning/struct-max-margin.hxx
index 55b03a1..f3d0b72 100644
--- a/include/opengm/learning/struct-max-margin.hxx
+++ b/include/opengm/learning/struct-max-margin.hxx
@@ -99,10 +99,11 @@ private:
 
 				// set the weights w in E(x,y) and F(x,y)
 				_dataset.getWeights() = w;
-
+                std::cout << std::endl << " MODEL : ";
 				for (int i = 0; i < _dataset.getNumberOfModels(); i++) {
+                    std::cout << i << " ";
 
-					// get E(x,y) and F(x,y)
+                    // get E(x,y) and F(x,y)
 					//std::cout << "locking model " << i << " of " << _dataset.getNumberOfModels() <<  std::endl;
 					_dataset.lockModel(i);
 					const GMType &     gm  = _dataset.getModel(i);
@@ -117,24 +118,24 @@ private:
 					// find the minimizer y* of F(y,w)
 					ConfigurationType mostViolated;
                     InferenceType inference(gml, _infParam);
-					inference.infer();
+                    inference.infer();
 					inference.arg(mostViolated);
 
 					// the optimal value of (1) is now c - F(y*,w)
-					value += c - gml.evaluate(mostViolated);
+                    value += c - gml.evaluate(mostViolated);
 
 					// the gradients are
 					typedef GradientAccumulator<Weights, ConfigurationType> GA;
-					GA gaBestEffort(gradient, bestEffort, GA::Add);
-					GA gaMostViolated(gradient, mostViolated, GA::Subtract);
-					for (size_t j = 0; j < gm.numberOfFactors(); j++) {
+                    GA gaBestEffort(gradient, bestEffort, GA::Add);
+                    GA gaMostViolated(gradient, mostViolated, GA::Subtract);
+                    for (size_t j = 0; j < gm.numberOfFactors(); j++) {
 
 						gm[j].callViFunctor(gaBestEffort);
 						gm[j].callViFunctor(gaMostViolated);
 					}
-
-					_dataset.unlockModel(i);
+                    _dataset.unlockModel(i);
 				}
+                std::cout << std::endl;
 			}
 
 		private:

From e19025f6d4832ac92a6868d1f1b8a217528be309 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Wed, 28 Oct 2015 21:45:08 +0100
Subject: [PATCH 10/19] lweightedsum_of_functions OPENGM_ASSERT corrected

---
 .../functions/learnable/lweightedsum_of_functions.hxx       | 5 +++--
 include/opengm/learning/gradient-accumulator.hxx            | 6 ------
 include/opengm/learning/struct-max-margin.hxx               | 6 +++---
 3 files changed, 6 insertions(+), 11 deletions(-)

diff --git a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
index 5978c52..62314f4 100644
--- a/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
+++ b/include/opengm/functions/learnable/lweightedsum_of_functions.hxx
@@ -77,10 +77,11 @@ LWeightedSumOfFunctions<T, I, L>::LWeightedSumOfFunctions
    :   shape_(shape), weights_(&weights), weightIDs_(weightIDs),feat_(feat)
 {
    OPENGM_ASSERT( weightIDs_.size() == feat_.size() );
-   for(size_t i=0; i<weightIDs_.size(); ++i)
+   for(size_t i=0; i<weightIDs_.size(); ++i){
       OPENGM_ASSERT( size() == feat_[i].size() );
       for(size_t j=0; j<dimension(); ++j)
-          OPENGM_ASSERT( shape(j) == feat_[i].shape(j))
+          OPENGM_ASSERT( shape_[j] == feat_[i].shape(j))
+   }
 }
 
 template <class T, class I, class L>
diff --git a/include/opengm/learning/gradient-accumulator.hxx b/include/opengm/learning/gradient-accumulator.hxx
index 43c9cf8..a13473d 100644
--- a/include/opengm/learning/gradient-accumulator.hxx
+++ b/include/opengm/learning/gradient-accumulator.hxx
@@ -97,8 +97,6 @@ struct FeatureAccumulator{
     }
 
     void resetWeights(){
-        //accFeaturesGt_ = 0.0;
-        //accWeights_ = 0.0;
         for(size_t i=0; i<accWeights_.size(); ++i){
             accWeights_[i] = 0.0;
         }
@@ -127,7 +125,6 @@ struct FeatureAccumulator{
                 const Accessor accessorGt(begin, end, gtLabel_);
                 const Accessor accessorMap(begin, end, mapLabel_);
                 
-
                 if(add_){
                     // for gt label
                     accWeights_[gwi] += weight_*f.weightGradient(wi, AccessorIter(accessorGt, 0));
@@ -172,9 +169,6 @@ struct FeatureAccumulator{
     double weight_;
 };
 
-
-
-
 }} // namespace opengm::learning
 
 #endif // OPENGM_LEARNING_GRADIENT_ACCUMULATOR_H__
diff --git a/include/opengm/learning/struct-max-margin.hxx b/include/opengm/learning/struct-max-margin.hxx
index f3d0b72..04f3ffd 100644
--- a/include/opengm/learning/struct-max-margin.hxx
+++ b/include/opengm/learning/struct-max-margin.hxx
@@ -104,8 +104,7 @@ private:
                     std::cout << i << " ";
 
                     // get E(x,y) and F(x,y)
-					//std::cout << "locking model " << i << " of " << _dataset.getNumberOfModels() <<  std::endl;
-					_dataset.lockModel(i);
+                    _dataset.lockModel(i);
 					const GMType &     gm  = _dataset.getModel(i);
 					const GMWITHLOSS & gml = _dataset.getModelWithLoss(i);
 
@@ -118,8 +117,9 @@ private:
 					// find the minimizer y* of F(y,w)
 					ConfigurationType mostViolated;
                     InferenceType inference(gml, _infParam);
+
                     inference.infer();
-					inference.arg(mostViolated);
+                    inference.arg(mostViolated);
 
 					// the optimal value of (1) is now c - F(y*,w)
                     value += c - gml.evaluate(mostViolated);

From 6fb911920d35ed5b266392b1e2fafd8b3cd33661 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Mon, 2 Nov 2015 19:51:49 +0100
Subject: [PATCH 11/19] adding normalized weights print output (only for check
 of convergence - not to be used in calculation)

---
 include/opengm/learning/bundle-optimizer.hxx | 16 ++++++++++------
 1 file changed, 10 insertions(+), 6 deletions(-)

diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index 4be57e8..9f7c094 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -200,18 +200,22 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		// minimal value of lower bound
 		T minLower;
 
-        std::cout << "w before findMinLowerBound: ";
-        for(size_t i=0; i<w.size(); ++i)
-            std::cout << w[i] << " ";
-        std::cout << std::endl;
-
         // update w and get minimal value
 		findMinLowerBound(w, minLower);
 
-		std::cout << " min_w ℒ(w)   + ½λ|w|²   is: " << minLower << std::endl;
+        // norm of w
+        double norm = 0.0;
+        for(size_t i=0; i<w.size(); ++i)
+            norm += w[i]*w[i];
+        norm = std::sqrt(norm);
+
+        std::cout << " min_w ℒ(w)   + ½λ|w|²   is: " << minLower << std::endl;
         std::cout << " w* of ℒ(w)   + ½λ|w|²   is: (";
         for(size_t i=0; i<w.size(); ++i)
             std::cout << w[i] << " ";
+        std::cout << ")              normalized: (";
+        for(size_t i=0; i<w.size(); ++i)
+            std::cout << w[i]/norm << " ";
         std::cout << ")" << std::endl;
 
 		// compute gap

From b04442e752b14521cfbfe1a9669fe01676009074 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Tue, 3 Nov 2015 18:47:21 +0100
Subject: [PATCH 12/19] paralellization added to struct-max-margin (triggered
 by WITH_OPENMP)

---
 .../opengm/learning/gradient-accumulator.hxx  |  2 +-
 include/opengm/learning/struct-max-margin.hxx | 38 ++++++++++++++++---
 2 files changed, 33 insertions(+), 7 deletions(-)

diff --git a/include/opengm/learning/gradient-accumulator.hxx b/include/opengm/learning/gradient-accumulator.hxx
index a13473d..88e920a 100644
--- a/include/opengm/learning/gradient-accumulator.hxx
+++ b/include/opengm/learning/gradient-accumulator.hxx
@@ -124,7 +124,7 @@ struct FeatureAccumulator{
 
                 const Accessor accessorGt(begin, end, gtLabel_);
                 const Accessor accessorMap(begin, end, mapLabel_);
-                
+
                 if(add_){
                     // for gt label
                     accWeights_[gwi] += weight_*f.weightGradient(wi, AccessorIter(accessorGt, 0));
diff --git a/include/opengm/learning/struct-max-margin.hxx b/include/opengm/learning/struct-max-margin.hxx
index 04f3ffd..6ff2685 100644
--- a/include/opengm/learning/struct-max-margin.hxx
+++ b/include/opengm/learning/struct-max-margin.hxx
@@ -5,6 +5,10 @@
 #include "bundle-optimizer.hxx"
 #include "gradient-accumulator.hxx"
 
+#ifdef WITH_OPENMP
+#include <omp.h>
+#endif
+
 namespace opengm {
 
 namespace learning {
@@ -100,12 +104,25 @@ private:
 				// set the weights w in E(x,y) and F(x,y)
 				_dataset.getWeights() = w;
                 std::cout << std::endl << " MODEL : ";
-				for (int i = 0; i < _dataset.getNumberOfModels(); i++) {
-                    std::cout << i << " ";
 
-                    // get E(x,y) and F(x,y)
+                #ifdef WITH_OPENMP
+                omp_lock_t modelLock;
+                omp_init_lock(&modelLock);
+                #pragma omp parallel for
+                #endif
+                for (int i = 0; i < _dataset.getNumberOfModels(); i++) {
+                    std::cout << i;
+
+                    // lock the model
+                    #ifdef WITH_OPENMP
+                    omp_set_lock(&modelLock);
                     _dataset.lockModel(i);
-					const GMType &     gm  = _dataset.getModel(i);
+                    omp_unset_lock(&modelLock);
+                    #else
+                    _dataset.lockModel(i);
+                    #endif
+                    // get E(x,y) and F(x,y)
+                    const GMType &     gm  = _dataset.getModel(i);
 					const GMWITHLOSS & gml = _dataset.getModelWithLoss(i);
 
 					// get the best-effort solution y'
@@ -122,6 +139,7 @@ private:
                     inference.arg(mostViolated);
 
 					// the optimal value of (1) is now c - F(y*,w)
+                    #pragma omp atomic
                     value += c - gml.evaluate(mostViolated);
 
 					// the gradients are
@@ -133,11 +151,19 @@ private:
 						gm[j].callViFunctor(gaBestEffort);
 						gm[j].callViFunctor(gaMostViolated);
 					}
+
+                    // unlock the model
+                    #ifdef WITH_OPENMP
+                    omp_set_lock(&modelLock);
+                    _dataset.unlockModel(i);
+                    omp_unset_lock(&modelLock);
+                    #else
                     _dataset.unlockModel(i);
-				}
-                std::cout << std::endl;
+                    #endif
+                } // end for model
 			}
 
+
 		private:
 
 			DatasetType& _dataset;

From b6a5d0d3893598a43dbc30876d225455c5496e09 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Thu, 5 Nov 2015 15:37:49 +0100
Subject: [PATCH 13/19] removed redundant print info

---
 include/opengm/datastructures/marray/marray.hxx | 1 -
 include/opengm/learning/bundle-optimizer.hxx    | 5 +----
 2 files changed, 1 insertion(+), 5 deletions(-)

diff --git a/include/opengm/datastructures/marray/marray.hxx b/include/opengm/datastructures/marray/marray.hxx
index 7871e7e..0c91d2f 100644
--- a/include/opengm/datastructures/marray/marray.hxx
+++ b/include/opengm/datastructures/marray/marray.hxx
@@ -15,7 +15,6 @@
 #include <iostream> // cout
 #include <memory> // allocator
 #include <numeric> // accumulate
-#include <typeinfo>
 
 /// Runtime-flexible multi-dimensional views and arrays
 namespace marray {
diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index 9f7c094..4642d71 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -157,7 +157,7 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
 		t++;
 
-        std::cout << std::endl << "-----------------------------------------------------------------------------> iteration      " << t << std::endl;
+        std::cout << std::endl << "----------------- iteration      " << t << std::endl;
 
         Weights w_tm1 = w;
 
@@ -213,9 +213,6 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
         std::cout << " w* of ℒ(w)   + ½λ|w|²   is: (";
         for(size_t i=0; i<w.size(); ++i)
             std::cout << w[i] << " ";
-        std::cout << ")              normalized: (";
-        for(size_t i=0; i<w.size(); ++i)
-            std::cout << w[i]/norm << " ";
         std::cout << ")" << std::endl;
 
 		// compute gap

From f24715a97cf400cab79761f10d4d6c77eb5adbaf Mon Sep 17 00:00:00 2001
From: Joerg Kappes <kappes@math.uni-heidelberg.de>
Date: Fri, 6 Nov 2015 07:53:48 +0100
Subject: [PATCH 14/19] Update README.md

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 020f22b..9b54a74 100644
--- a/README.md
+++ b/README.md
@@ -3,6 +3,8 @@ OpenGM 2
 
 [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm)
 
+[![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/opengm)
+
 
 -----------------------------------------------------------------------------------------------
 

From f8efc9cfb46e45b0850580df38201022b7521c26 Mon Sep 17 00:00:00 2001
From: Joerg Kappes <kappes@math.uni-heidelberg.de>
Date: Fri, 6 Nov 2015 07:54:23 +0100
Subject: [PATCH 15/19] Update README.md

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 9b54a74..9c12007 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,9 @@
 OpenGM 2
 ========
 
-[![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm)
+master: [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm)
 
-[![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/opengm)
+learning-experimental: [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/opengm)
 
 
 -----------------------------------------------------------------------------------------------

From 298b409c56b3aa9162f431b4e2d89400edca88ac Mon Sep 17 00:00:00 2001
From: Joerg Kappes <kappes@math.uni-heidelberg.de>
Date: Fri, 6 Nov 2015 07:55:15 +0100
Subject: [PATCH 16/19] Update README.md

---
 README.md | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 9c12007..d1709e1 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,8 @@
 OpenGM 2
 ========
 
-master: [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm)
-
-learning-experimental: [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/opengm)
+master:                [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm)
+learning-experimental: [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/learning-experimental)
 
 
 -----------------------------------------------------------------------------------------------

From 7c1b6f0012983b841af0b3ac327f2d8dc7acaa16 Mon Sep 17 00:00:00 2001
From: opengm <opengm@hci.iwr.uni-heidelberg.de>
Date: Fri, 6 Nov 2015 08:03:03 +0100
Subject: [PATCH 17/19] Update README.md

---
 README.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index d1709e1..77e4d40 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,9 @@
 OpenGM 2
 ========
 
-master:                [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm)
-learning-experimental: [![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/learning-experimental)
+[![Build Status](https://travis-ci.org/opengm/opengm.png?branch=master)](https://travis-ci.org/opengm/opengm) (master)
+
+[![Build Status](https://travis-ci.org/opengm/opengm.png?branch=learning-experimental)](https://travis-ci.org/opengm/opengm) (learning-experimental)
 
 
 -----------------------------------------------------------------------------------------------

From 442228dc4b9bba2df88bc128f74ce2fd34c27797 Mon Sep 17 00:00:00 2001
From: DerThorsten <thorsten.beier@iwr.uni-heidelberg.de>
Date: Mon, 9 Nov 2015 09:08:21 +0100
Subject: [PATCH 18/19] minor fix

---
 src/interfaces/python/opengm/learning/CMakeLists.txt | 2 +-
 src/interfaces/python/opengm/learning/learning.cxx   | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/interfaces/python/opengm/learning/CMakeLists.txt b/src/interfaces/python/opengm/learning/CMakeLists.txt
index 05bc47c..a594ea4 100644
--- a/src/interfaces/python/opengm/learning/CMakeLists.txt
+++ b/src/interfaces/python/opengm/learning/CMakeLists.txt
@@ -24,7 +24,7 @@ set(PY_OPENGM_CORE_SOURCES
             pyDataset.cxx
             pyLoss.cxx
             pyGridSearchLearner.cxx
-            pyMaxLikelihoodLearner.cxx
+            #pyMaxLikelihoodLearner.cxx
             pyStructMaxMarginLearner.cxx
             pySubgradientSSVM.cxx
             pyStructPerceptron.cxx
diff --git a/src/interfaces/python/opengm/learning/learning.cxx b/src/interfaces/python/opengm/learning/learning.cxx
index a45d3a9..195b2ac 100644
--- a/src/interfaces/python/opengm/learning/learning.cxx
+++ b/src/interfaces/python/opengm/learning/learning.cxx
@@ -37,8 +37,8 @@ namespace opengm{
     template<class DATASET, class OPTIMIZER>
     void export_struct_max_margin_bundle_learner(const std::string & clsName);
 
-    template<class DATASET>
-    void export_max_likelihood_learner(const std::string & clsName);
+    //template<class DATASET>
+    //void export_max_likelihood_learner(const std::string & clsName);
 
     template<class DATASET>
     void export_struct_perceptron_learner(const std::string & clsName);
@@ -82,7 +82,7 @@ BOOST_PYTHON_MODULE_INIT(_learning) {
     opengm::export_grid_search_learner<op::GmAdderFlexibleLossDataset>("GridSearch_FlexibleLoss");
     opengm::export_struct_perceptron_learner<op::GmAdderFlexibleLossDataset>("StructPerceptron_FlexibleLoss");
     opengm::export_subgradient_ssvm_learner<op::GmAdderFlexibleLossDataset>("SubgradientSSVM_FlexibleLoss");
-    opengm::export_max_likelihood_learner<op::GmAdderFlexibleLossDataset>("MaxLikelihood_FlexibleLoss");
+    //opengm::export_max_likelihood_learner<op::GmAdderFlexibleLossDataset>("MaxLikelihood_FlexibleLoss");
     opengm::export_rws_learner<op::GmAdderFlexibleLossDataset>("Rws_FlexibleLoss");
     
     #if defined(WITH_CPLEX) || defined(WITH_GUROBI)

From 7bc0d74a056e1b3a231c25ca86f98f00dfb83941 Mon Sep 17 00:00:00 2001
From: Janez Ales <janez.ales@iwr.uni-heidelberg.de>
Date: Mon, 23 Nov 2015 17:07:19 +0100
Subject: [PATCH 19/19] verbose=false implemented in more detail

---
 include/opengm/learning/bundle-optimizer.hxx  | 72 +++++++++++--------
 include/opengm/learning/solver/CplexBackend.h |  7 +-
 include/opengm/learning/struct-max-margin.hxx | 10 ++-
 3 files changed, 57 insertions(+), 32 deletions(-)

diff --git a/include/opengm/learning/bundle-optimizer.hxx b/include/opengm/learning/bundle-optimizer.hxx
index 4642d71..e8e5a7e 100644
--- a/include/opengm/learning/bundle-optimizer.hxx
+++ b/include/opengm/learning/bundle-optimizer.hxx
@@ -12,14 +12,14 @@ namespace learning {
 //template <typename T>
 //std::ostream& operator<<(std::ostream& out, Weights<T>& w) {
 
-	//out << "[";
-	//for (int i = 0; i < w.numberOfWeights(); i++) {
-
-		//if (i > 0)
-			//out << ", ";
-		//out << w[i];
-	//}
-	//out << "]";
+//    out << "[";
+//    for (int i = 0; i < w.numberOfWeights(); i++) {
+
+//        if (i > 0)
+//            out << ", ";
+//        out << w[i];
+//    }
+//    out << "]";
 //}
 
 enum OptimizerResult {
@@ -157,14 +157,17 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
 		t++;
 
-        std::cout << std::endl << "----------------- iteration      " << t << std::endl;
+        if(oracle.getInfParam().verbose_ )
+            std::cout << std::endl << "----------------- iteration      " << t << std::endl;
 
         Weights w_tm1 = w;
 
-        std::cout << "w: ";
-        for(size_t i=0; i<w_tm1.size(); ++i)
-            std::cout << w_tm1[i] << " ";
-        std::cout << std::endl;
+        if(oracle.getInfParam().verbose_ ){
+            std::cout << "w: ";
+            for(size_t i=0; i<w_tm1.size(); ++i)
+                std::cout << w_tm1[i] << " ";
+            std::cout << std::endl;
+        }
 
 		// value of L at current w
 		T L_w_tm1 = 0.0;
@@ -175,24 +178,29 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 		// get current value and gradient
 		oracle(w_tm1, L_w_tm1, a_t);
 
-		std::cout << "       L(w)              is: " << L_w_tm1 << std::endl;
-        std::cout << "∂L(w)/∂:  (";
-        for(size_t i=0; i<a_t.size(); ++i)
-            std::cout << a_t[i] << " ";
-        std::cout << ")" << std::endl;
+        if(oracle.getInfParam().verbose_ ){
+            std::cout << "       L(w)              is: " << L_w_tm1 << std::endl;
+            std::cout << "∂L(w)/∂:  (";
+            for(size_t i=0; i<a_t.size(); ++i)
+                std::cout << a_t[i] << " ";
+            std::cout << ")" << std::endl;
+        }
 
 		// update smallest observed value of regularized L
 		minValue = std::min(minValue, L_w_tm1 + _parameter.lambda*0.5*dot(w_tm1, w_tm1));
 
-		std::cout << " min_i L(w_i) + ½λ|w_i|² is: " << minValue << std::endl;
+        if(oracle.getInfParam().verbose_ )
+            std::cout << " min_i L(w_i) + ½λ|w_i|² is: " << minValue << std::endl;
 
 		// compute hyperplane offset
 		T b_t = L_w_tm1 - dot(w_tm1, a_t);
 
-        std::cout << "adding hyperplane: ( ";
-        for(size_t i=0; i<a_t.size(); ++i)
-            std::cout << a_t[i] << " ";
-        std::cout << ")*w + " << b_t << std::endl;
+        if(oracle.getInfParam().verbose_ ){
+            std::cout << "adding hyperplane: ( ";
+            for(size_t i=0; i<a_t.size(); ++i)
+                std::cout << a_t[i] << " ";
+            std::cout << ")*w + " << b_t << std::endl;
+        }
 
 		// update lower bound
 		_bundleCollector.addHyperplane(a_t, b_t);
@@ -209,11 +217,16 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
             norm += w[i]*w[i];
         norm = std::sqrt(norm);
 
-        std::cout << " min_w ℒ(w)   + ½λ|w|²   is: " << minLower << std::endl;
-        std::cout << " w* of ℒ(w)   + ½λ|w|²   is: (";
-        for(size_t i=0; i<w.size(); ++i)
-            std::cout << w[i] << " ";
-        std::cout << ")" << std::endl;
+        if(oracle.getInfParam().verbose_ ){
+            std::cout << " min_w ℒ(w)   + ½λ|w|²   is: " << minLower << std::endl;
+            std::cout << " w* of ℒ(w)   + ½λ|w|²   is: (";
+            for(size_t i=0; i<w.size(); ++i)
+                std::cout << w[i] << " ";
+            std::cout << ")              normalized: (";
+            for(size_t i=0; i<w.size(); ++i)
+                std::cout << w[i]/norm << " ";
+            std::cout << ")" << std::endl;
+        }
 
 		// compute gap
 		T eps_t;
@@ -224,7 +237,8 @@ BundleOptimizer<T>::optimize(Oracle& oracle, Weights& w) {
 
 		lastMinLower = minLower;
 
-		std::cout  << "          ε   is: " << eps_t << std::endl;
+        if(oracle.getInfParam().verbose_ )
+            std::cout  << "          ε   is: " << eps_t << std::endl;
 
 		// converged?
 		if (eps_t <= _parameter.min_eps)
diff --git a/include/opengm/learning/solver/CplexBackend.h b/include/opengm/learning/solver/CplexBackend.h
index b4819e5..feda3f4 100644
--- a/include/opengm/learning/solver/CplexBackend.h
+++ b/include/opengm/learning/solver/CplexBackend.h
@@ -336,7 +336,8 @@ CplexBackend::solve(Solution& x, double& value, std::string& msg) {
            return false;
         }
         else
-            msg = "Optimal solution found";
+            if(_parameter.verbose == true)
+                msg = "Optimal solution found";
 
         // extract solution
         cplex_.getValues(sol_, x_);
@@ -412,12 +413,16 @@ CplexBackend::setVerbose(bool verbose) {
         cplex_.setParam(IloCplex::MIPDisplay, 1);
         cplex_.setParam(IloCplex::SimDisplay, 1);
         cplex_.setParam(IloCplex::SiftDisplay, 1);
+        cplex_.setParam(IloCplex::BarDisplay, 1);
+        cplex_.setParam(IloCplex::NetDisplay, 1);
     }
     else
     {
         cplex_.setParam(IloCplex::MIPDisplay, 0);
         cplex_.setParam(IloCplex::SimDisplay, 0);
         cplex_.setParam(IloCplex::SiftDisplay, 0);
+        cplex_.setParam(IloCplex::BarDisplay, 0);
+        cplex_.setParam(IloCplex::NetDisplay, 0);
     }
 }
 
diff --git a/include/opengm/learning/struct-max-margin.hxx b/include/opengm/learning/struct-max-margin.hxx
index 6ff2685..815c0aa 100644
--- a/include/opengm/learning/struct-max-margin.hxx
+++ b/include/opengm/learning/struct-max-margin.hxx
@@ -103,7 +103,9 @@ private:
 
 				// set the weights w in E(x,y) and F(x,y)
 				_dataset.getWeights() = w;
-                std::cout << std::endl << " MODEL : ";
+
+                if(_infParam.verbose_ )
+                    std::cout << std::endl << " MODEL : ";
 
                 #ifdef WITH_OPENMP
                 omp_lock_t modelLock;
@@ -111,7 +113,8 @@ private:
                 #pragma omp parallel for
                 #endif
                 for (int i = 0; i < _dataset.getNumberOfModels(); i++) {
-                    std::cout << i;
+                    if(_infParam.verbose_ )
+                        std::cout << i;
 
                     // lock the model
                     #ifdef WITH_OPENMP
@@ -163,6 +166,9 @@ private:
                 } // end for model
 			}
 
+            const typename InferenceType::Parameter& getInfParam(){
+                return _infParam;
+            }
 
 		private: