The exponential increase in carbon-dioxide resulting Global Warming would make the planet earth to become inhabitable in many parts of the world with ensuing mass starvation. The rise of digital technology all over the world fundamentally have changed the lives of humans. The emerging technology of the Internet of Things, IoT, machine learning, data mining, biotechnology, biometric, and deep le...

Abstract A Stacked Autoencoder Extreme learning machine (SAE-ELM) assessment model is proposed to study the weight of an Unmanned Combat Air Vehicle (UCAV) situation assessment. On basis existing air combat description parameters and their optimized advantage function weights, mapping relationship between weights established by using SAE-ELM achieve a more accurate evaluation. From four error i...

Many studies have been undertaken by using machine learning techniques, including neural networks, to predict stock returns. Recently, a method known as deep learning, which achieves high performance mainly in image recognition and speech recognition, has attracted attention in the machine learning field. This paper implements deep learning to predict one-month-ahead stock returns in the cross-...

Privacy preserving multi-party machine learning approaches enable multiple parties to train a machine learning model from aggregate data while ensuring the privacy of their individual datasets is preserved. In this paper, we propose a privacy preserving multi-party machine learning approach based on homomorphic encryption where the machine learning algorithm of choice is deep neural networks. W...

We first look at a high-level comparison between deep learning and standard machine learning techniques (like graphical models). The empirical goal in deep learning is usually that of classification or feature learning, whereas in graphical models we are often interested in transfer learning and latent variable inference. The main learning algorithm in deep learning is back-propagation whereas ...