Gradient Ascent

• To maximize loss function unlike Gradient Descent
• Proportional to positive of gradient
• ${\theta }_{t+1}=\theta t+{\eta }_t{\Sigma }_{n=1}^N(\nabla l_n({\theta }_t){)}^T$