1 citations · 1 across the 5 of their papers we have counts for
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A Low-complexity Brain-computer Interface for High-complexity Robot Swarm Control
Gregory Canal, Yancy Diaz-Mercado, Magnus Egerstedt +1
A brain-computer interface (BCI) is a system that allows a human operator to use only mental commands in controlling end effectors that interact with the world around them. Such a…
Late fusion of machine learning models using passively captured interpersonal social interactions and motion from smartphones predicts decompensation in heart failure
Ayse S. Cakmak, Samuel Densen, Gabriel Najarro +5
Objective: Worldwide, heart failure (HF) is a major cause of morbidity and mortality and one of the leading causes of hospitalization. Early detection of HF symptoms and pro-active…
Sparse Bayesian Learning with Dynamic Filtering for Inference of Time-Varying Sparse Signals
Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher J. Rozell
Many signal processing applications require estimation of time-varying sparse signals, potentially with the knowledge of an imperfect dynamics model. In this paper, we propose an a…
Efficient Tracking of Sparse Signals via an Earth Mover's Distance Dynamics Regularizer
Nicholas P. Bertrand, Adam S. Charles, John Lee +2
Tracking algorithms such as the Kalman filter aim to improve inference performance by leveraging the temporal dynamics in streaming observations. However, the tracking regularizers…