| fEpsilon | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| fPastSquaredBiasGradients | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| fPastSquaredWeightGradients | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| fWorkBiasTensor | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| fWorkWeightTensor | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| GetEpsilon() const | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | inline |
| GetPastSquaredBiasGradients() | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | inline |
| GetPastSquaredBiasGradientsAt(size_t i) | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | inline |
| GetPastSquaredWeightGradients() | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | inline |
| GetPastSquaredWeightGradientsAt(size_t i) | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | inline |
| Matrix_t typedef | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | |
| Scalar_t typedef | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | |
| TAdagrad(DeepNet_t &deepNet, Scalar_t learningRate=0.01, Scalar_t epsilon=1e-8) | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | |
| UpdateBiases(size_t layerIndex, std::vector< Matrix_t > &biases, const std::vector< Matrix_t > &biasGradients) | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| UpdateWeights(size_t layerIndex, std::vector< Matrix_t > &weights, const std::vector< Matrix_t > &weightGradients) | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | protected |
| ~TAdagrad()=default | TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t > | |
