We simulate and program our architecture on a Xilinx Virtex 7 FPGA. The architectural implementation for a single neuron Q-learning and a more complex Multilayer Perception (MLP) Q-learning ...

Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks and problem domains. However, the success of DNNs depends on the proper configuration of its architecture and ...

An Internet of Things (IoT) platform is a software architecture that enables the connection, management, and analysis of IoT devices, sensors, and data. It provides a centralized system for IoT ...

Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations Jacob A. Zwart 1 * Jeremy Diaz 1 Scott Hamshaw 1 Samantha Oliver 2 Jesse ...

Choisir la meilleure architecture pour votre modèle de deep learning n’est pas une tâche triviale. Vous devez prendre en compte de nombreux facteurs, tels que le type et la taille de vos ...

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically ...

Deep learning architectures, specifically Deep Momentum Networks (DMNs) , have been found to be an effective approach to momentum and mean-reversion trading. However, some of the key challenges in ...

Most approaches for improving deep reinforcement learning performance focus on the learning algorithm itself while using standard neural networks not necessarily designed for reinforcement learning.

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Topics Spotlight: AI-ready data centers ...