मोमेंटम के साथ ग्रेडिएंट डिसेंट

इनपुट:
double beta = 0.9;
std::vector<double> weights = {0.0};
std::vector<std::vector<double>> gradients = {
    {1.0},
    {1.0},
    {1.0}
};
double learning_rate = 0.1;

अपेक्षित आउटपुट:
std::vector<double> expected = {-0.561};

इनपुट:
double beta = 0.9;
double[] weights = new double[] {0.0};
double[][] gradients = new double[][] {
    new double[] {1.0},
    new double[] {1.0},
    new double[] {1.0}
};
double learning_rate = 0.1;

अपेक्षित आउटपुट:
double[] expected = new double[] {-0.561};

इनपुट:
double beta = 0.0;
std::vector<double> weights = {1.0, 1.0};
std::vector<std::vector<double>> gradients = {
    {2.0, -4.0}
};
double learning_rate = 0.5;

अपेक्षित आउटपुट:
std::vector<double> expected = {0.0, 3.0};

इनपुट:
double beta = 0.0;
double[] weights = new double[] {1.0, 1.0};
double[][] gradients = new double[][] {
    new double[] {2.0, -4.0}
};
double learning_rate = 0.5;

अपेक्षित आउटपुट:
double[] expected = new double[] {0.0, 3.0};