171 citations · 937 across the 54 of their papers we have counts for
4 papers · 1 filter
Identifying Bias in AI using Simulation
Daniel McDuff, Roger Cheng, Ashish Kapoor
Machine learned models exhibit bias, often because the datasets used to train them are biased. This presents a serious problem for the deployment of such technology, as the resulti…
Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility
Benjamin Hepp, Debadeepta Dey, Sudipta N. Sinha +3
Camera equipped drones are nowadays being used to explore large scenes and reconstruct detailed 3D maps. When free space in the scene is approximately known, an offline planner can…
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Daniel McDuff, Ashish Kapoor
As people learn to navigate the world, autonomic nervous system (e.g., "fight or flight") responses provide intrinsic feedback about the potential consequence of action choices (e.…
Verifying Controllers Against Adversarial Examples with Bayesian Optimization
Shromona Ghosh, Felix Berkenkamp, Gireeja Ranade +2
Recent successes in reinforcement learning have lead to the development of complex controllers for real-world robots. As these robots are deployed in safety-critical applications a…