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Deluca – A Differentiable Control Library: Environments, Methods, and Benchmarking
We present an open-source library of natively differentiable physics and...
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Machine Learning for Mechanical Ventilation Control
We consider the problem of controlling an invasive mechanical ventilator...
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Stochastic Optimization with Laggard Data Pipelines
State-of-the-art optimization is steadily shifting towards massively par...
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Disentangling Adaptive Gradient Methods from Learning Rates
We investigate several confounding factors in the evaluation of optimiza...
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A Deep Conditioning Treatment of Neural Networks
We study the role of depth in training randomly initialized overparamete...
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Logarithmic Regret for Online Control
We study optimal regret bounds for control in linear dynamical systems u...
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Boosting for Dynamical Systems
We propose a framework of boosting for learning and control in environme...
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Design and Development of Underwater Vehicle: ANAHITA
Anahita is an autonomous underwater vehicle which is currently being dev...
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Online Control with Adversarial Disturbances
We study the control of a linear dynamical system with adversarial distu...
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Extreme Tensoring for Low-Memory Preconditioning
State-of-the-art models are now trained with billions of parameters, rea...
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The Case for Full-Matrix Adaptive Regularization
Adaptive regularization methods come in diagonal and full-matrix variant...
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cpSGD: Communication-efficient and differentially-private distributed SGD
Distributed stochastic gradient descent is an important subroutine in di...
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Effective Dimension of Exp-concave Optimization
We investigate the role of the effective (a.k.a. statistical) dimension ...
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Leverage Score Sampling for Faster Accelerated Regression and ERM
Given a matrix A∈R^n× d and a vector b ∈R^d, we show how to compute an ϵ...
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Lower Bounds for Higher-Order Convex Optimization
State-of-the-art methods in convex and non-convex optimization employ hi...
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The Price of Differential Privacy For Online Learning
We design differentially private algorithms for the problem of online li...
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Finding Approximate Local Minima Faster than Gradient Descent
We design a non-convex second-order optimization algorithm that is guara...
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Second-Order Stochastic Optimization for Machine Learning in Linear Time
First-order stochastic methods are the state-of-the-art in large-scale m...
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Multisection in the Stochastic Block Model using Semidefinite Programming
We consider the problem of identifying underlying community-like structu...
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