Cross-entropy loss measures the difference between the predicted probabilities and the true labels of a classification task. It is also known as log loss or negative log likelihood. The formula ...

But when Tensorflow has made a wheel then why to reinvent the same wheel. The Tensorflow provides several APIs for the cross entropy losses. Now the key difference between tf.nn and tf.losses - is ...

The connection explains the rational behind softmax cross-entropy from information-theoretic perspective, which brings a new insight to understand the classifiers. We utilise the connection between ...

Abstract: The cross-entropy method is an efficient and general optimization algorithm. However, its applicability in reinforcement learning (RL) seems to be limited because it often converges to ...

For compressing CNNs, we propose an efficient and robust pruning approach, cross-entropy pruning (CEP). Given a trained CNN model, connections were divided into groups in a group-wise way according to ...