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Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces
Garrett Warnell, Nicholas Waytowich, Vernon Lawhern +1
While recent advances in deep reinforcement learning have allowed autonomous learning agents to succeed at a variety of complex tasks, existing algorithms generally require a lot o…
EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features
Dongrui Wu, Brent J. Lance, Vernon J. Lawhern +3
Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first ti…
Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization
Dongrui Wu, Vernon J. Lawhern, W. David Hairston +1
Electroencephalography (EEG) headsets are the most commonly used sensing devices for Brain-Computer Interface. In real-world applications, there are advantages to extrapolating dat…
Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
One big challenge that hinders the transition of brain-computer interfaces (BCIs) from laboratory settings to real-life applications is the availability of high-performance and rob…