void function ( int arg0 , int arg1 , double arg2 ) { constraints . add ( new Constraint ( arg0 , arg1 , arg2 ) ) ; }
this adds a constraint on the weight vector , that a certain component must be set to a sparse index = value concode_field_sep ConcatVector localDerivative concode_elem_sep AbstractDifferentiableFunction<T> fn concode_elem_sep TrainingWorker mainWorker concode_elem_sep Object naturalTerminationBarrier concode_elem_sep long cpuTimeRequired concode_elem_sep boolean quiet concode_elem_sep double value concode_elem_sep boolean isFinished concode_elem_sep double[] arr concode_elem_sep boolean useThreads concode_elem_sep long finishedAtTime concode_elem_sep OptimizationState optimizationState concode_elem_sep List<Constraint> constraints concode_elem_sep boolean isSparse concode_elem_sep int index concode_elem_sep double convergenceDerivativeNorm concode_elem_sep double localLogLikelihood concode_elem_sep ConcatVector weights concode_elem_sep int numThreads concode_elem_sep int component concode_elem_sep int threadIdx concode_elem_sep Redwood.RedwoodChannels log concode_elem_sep long jvmThreadId concode_elem_sep T[] dataset concode_elem_sep double l2regularization concode_elem_sep List<T> queue concode_field_sep int estimateRelativeRuntime concode_elem_sep ConcatVector optimize concode_elem_sep ConcatVector optimize concode_elem_sep void addDenseConstraint concode_elem_sep void run concode_elem_sep void run concode_elem_sep OptimizationState getFreshOptimizationState concode_elem_sep void applyToWeights concode_elem_sep void applyToDerivative concode_elem_sep boolean updateWeights