96 citations · 396 across the 27 of their papers we have counts for
6 papers · 1 filter
Machine Learning for Mechanical Ventilation Control (Extended Abstract)
Daniel Suo, Naman Agarwal, Wenhan Xia +12
Mechanical ventilation is one of the most widely used therapies in the ICU. However, despite broad application from anaesthesia to COVID-related life support, many injurious challe…
A Boosting Approach to Reinforcement Learning
Nataly Brukhim, Elad Hazan, Karan Singh
Reducing reinforcement learning to supervised learning is a well-studied and effective approach that leverages the benefits of compact function approximation to deal with large-sca…
A Regret Minimization Approach to Iterative Learning Control
Naman Agarwal, Elad Hazan, Anirudha Majumdar +1
We consider the setting of iterative learning control, or model-based policy learning in the presence of uncertain, time-varying dynamics. In this setting, we propose a new perform…
Deluca -- A Differentiable Control Library: Environments, Methods, and Benchmarking
Paula Gradu, John Hallman, Daniel Suo +7
We present an open-source library of natively differentiable physics and robotics environments, accompanied by gradient-based control methods and a benchmark-ing suite. The introdu…
Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
We consider the decision-making framework of online convex optimization with a very large number of experts. This setting is ubiquitous in contextual and reinforcement learning pro…
Machine Learning for Mechanical Ventilation Control
Daniel Suo, Naman Agarwal, Wenhan Xia +12
We consider the problem of controlling an invasive mechanical ventilator for pressure-controlled ventilation: a controller must let air in and out of a sedated patient's lungs acco…