18 citations · 74 across the 36 of their papers we have counts for
4 papers · 1 filter
Learning from Observations Using a Single Video Demonstration and Human Feedback
Sunil Gandhi, Tim Oates, Tinoosh Mohsenin +1
In this paper, we present a method for learning from video demonstrations by using human feedback to construct a mapping between the standard representation of the agent and the vi…
Minimizing Classification Energy of Binarized Neural Network Inference for Wearable Devices
Morteza Hosseini, Hirenkumar Paneliya, Uttej Kallakuri +2
In this paper, we propose a low-power hardware for efficient deployment of binarized neural networks (BNNs) that have been trained for physiological datasets. BNNs constrain weight…
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning
Bharat Prakash, Mark Horton, Nicholas R. Waytowich +3
In autonomous embedded systems, it is often vital to reduce the amount of actions taken in the real world and energy required to learn a policy. Training reinforcement learning age…
Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention
Bharat Prakash, Mohit Khatwani, Nicholas Waytowich +1
Recent progress in AI and Reinforcement learning has shown great success in solving complex problems with high dimensional state spaces. However, most of these successes have been…