Search Results for author: Edgar Minasyan

Found 6 papers, 1 papers with code

Faster Projection-free Online Learning

no code implementations30 Jan 2020 Elad Hazan, Edgar Minasyan

In many online learning problems the computational bottleneck for gradient-based methods is the projection operation.

Adaptive Regret for Control of Time-Varying Dynamics

no code implementations8 Jul 2020 Paula Gradu, Elad Hazan, Edgar Minasyan

Our main contribution is a novel efficient meta-algorithm: it converts a controller with sublinear regret bounds into one with sublinear {\it adaptive regret} bounds in the setting of time-varying linear dynamical systems.

Machine Learning for Mechanical Ventilation Control

2 code implementations12 Feb 2021 Daniel Suo, Naman Agarwal, Wenhan Xia, Xinyi Chen, Udaya Ghai, Alexander Yu, Paula Gradu, Karan Singh, Cyril Zhang, Edgar Minasyan, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, Elad Hazan

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 according to a trajectory of airway pressures specified by a clinician.

BIG-bench Machine Learning

Provable Regret Bounds for Deep Online Learning and Control

no code implementations15 Oct 2021 Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan

The theory of deep learning focuses almost exclusively on supervised learning, non-convex optimization using stochastic gradient descent, and overparametrized neural networks.

Second-order methods

Online Control of Unknown Time-Varying Dynamical Systems

no code implementations NeurIPS 2021 Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan

On the positive side, we give an efficient algorithm that attains a sublinear regret bound against the class of Disturbance Response policies up to the aforementioned system variability term.

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