Search Results for author:
Found 3 papers, 2 papers with code
Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
Using a generated synthetic email promo dataset, we demonstrate similar prediction accuracies for (a) a wide and deep network that takes identifying information (or other categorical features) as input to the wide part and (b) a deep-only neural network that includes embeddings of categorical features in the input.
A Deep Learning Approach for Masking Fetal Gender in Ultrasound Images
Ultrasound (US) imaging is highly effective with regards to both cost and versatility in real-time diagnosis; however, determination of fetal gender by US scan in the early stages of pregnancy is also a cause of sex-selective abortion.
Evolving Deep Neural Networks
The success of deep learning depends on finding an architecture to fit the task.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
