Deep Learning for Heart Rate Estimation From Reflectance Photoplethysmography With Acceleration Power Spectrum and Acceleration Intensity

Acceleration of Deep Learning on FPGA

In recent years, deep convolutional neural networks (ConvNet) have shown their popularity in various real world applications. To provide more accurate results, the state-of-the-art ConvNet requires millions of parameters and billions of operations to process a single image, which represents a computational challenge for general purpose processors. As a result, hardware accelerators such as Grap...

ADC: Automated Deep Compression and Acceleration with Reinforcement Learning

Model compression is an effective technique facilitating the deployment of neural network models on mobile devices that have limited computation resources and a tight power budget. However, conventional model compression techniques [19, 20, 23] use hand-crafted features and require domain experts to explore the large design space trading off model size, speed, and accuracy, which is usually sub...

Hardware Acceleration for Power Efficient Deep Packet Inspection

Continuous Deep Q-Learning with Model-based Acceleration: Appendix

The iLQG algorithm optimizes trajectories by iteratively constructing locally optimal linear feedback controllers under a local linearization of the dynamics p(xt+1|xt,ut) = N (fxtxt + futut,Ft) and a quadratic expansion of the rewards r(xt,ut) (Tassa et al., 2012). Under linear dynamics and quadratic rewards, the action-value function Q(xt,ut) and value function V (xt) are locally quadratic an...

Continuous Deep Q-Learning with Model-based Acceleration

Model-free reinforcement learning has been successfully applied to a range of challenging problems, and has recently been extended to handle large neural network policies and value functions. However, the sample complexity of modelfree algorithms, particularly when using highdimensional function approximators, tends to limit their applicability to physical systems. In this paper, we explore alg...