
Safely Learning to Control the Constrained Linear Quadratic Regulator
We study the constrained linear quadratic regulator with unknown dynamic...
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Learning Linear Dynamical Systems with SemiParametric Least Squares
We analyze a simple prefiltered variation of the least squares estimator...
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Recommendations and User Agency: The Reachability of CollaborativelyFiltered Information
Recommender systems often rely on models which are trained to maximize a...
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A Tour of Reinforcement Learning: The View from Continuous Control
This manuscript surveys reinforcement learning from the perspective of o...
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A systematic framework for natural perturbations from videos
We introduce a systematic framework for quantifying the robustness of cl...
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Neural Kernels Without Tangents
We investigate the connections between neural networks and simple buildi...
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The Effect of Natural Distribution Shift on Question Answering Models
We build four new test sets for the Stanford Question Answering Dataset ...
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Certainty Equivalent Control of LQR is Efficient
We study the performance of the certainty equivalent controller on the L...
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Model Similarity Mitigates Test Set Overuse
Excessive reuse of test data has become commonplace in today's machine l...
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The Gap Between ModelBased and ModelFree Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
The effectiveness of modelbased versus modelfree methods is a longsta...
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Robust Guarantees for PerceptionBased Control
Motivated by vision based control of autonomous vehicles, we consider th...
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Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
We consider adaptive control of the Linear Quadratic Regulator (LQR), wh...
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A SuccessiveElimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
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Firstorder Methods Almost Always Avoid Saddle Points
We establish that firstorder methods avoid saddle points for almost all...
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On the Sample Complexity of the Linear Quadratic Regulator
This paper addresses the optimal control problem known as the Linear Qua...
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Flare Prediction Using Photospheric and Coronal Image Data
The precise physical process that triggers solar flares is not currently...
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The Marginal Value of Adaptive Gradient Methods in Machine Learning
Adaptive optimization methods, which perform local optimization with a m...
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On the Gap Between StrictSaddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation
We prove a query complexity lower bound on rankone principal component ...
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The Simulator: Understanding Adaptive Sampling in the ModerateConfidence Regime
We propose a novel technique for analyzing adaptive sampling called the ...
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Saturating Splines and Feature Selection
We extend the adaptive regression spline model by incorporating saturati...
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Gradient Descent Learns Linear Dynamical Systems
We prove that gradient descent efficiently converges to the global optim...
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CYCLADES: Conflictfree Asynchronous Machine Learning
We present CYCLADES, a general framework for parallelizing stochastic op...
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On kernel methods for covariates that are rankings
Permutationvalued features arise in a variety of applications, either i...
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BestofK Bandits
This paper studies the BestofK Bandit game: At each time the player ch...
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Large Scale Kernel Learning using Block Coordinate Descent
We demonstrate that distributed block coordinate descent can quickly sol...
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Gradient Descent Converges to Minimizers
We show that gradient descent converges to a local minimizer, almost sur...
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Train faster, generalize better: Stability of stochastic gradient descent
We show that parametric models trained by a stochastic gradient method (...
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Isometric sketching of any set via the Restricted Isometry Property
In this paper we show that for the purposes of dimensionality reduction ...
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Signal Recovery in Unions of Subspaces with Applications to Compressive Imaging
In applications ranging from communications to genetics, signals can be ...
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Query Complexity of DerivativeFree Optimization
This paper provides lower bounds on the convergence rate of Derivative F...
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Beneath the valley of the noncommutative arithmeticgeometric mean inequality: conjectures, casestudies, and consequences
Randomized algorithms that base iterationlevel decisions on samples fro...
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Tight Measurement Bounds for Exact Recovery of Structured Sparse Signals
Standard compressive sensing results state that to exactly recover an s ...
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Necessary and Sufficient Conditions for Success of the Nuclear Norm Heuristic for Rank Minimization
Minimizing the rank of a matrix subject to constraints is a challenging ...
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LeastSquares Temporal Difference Learning for the Linear Quadratic Regulator
Reinforcement learning (RL) has been successfully used to solve many con...
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Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis
In this project, we build a modular, scalable system that can collect, s...
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An example of how false conclusions could be made with personalized health tracking and suggestions for avoiding similar situations
Personalizing interventions and treatments is a necessity for optimal me...
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Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
We prove that the ordinary leastsquares (OLS) estimator attains nearly ...
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FiniteData Performance Guarantees for the OutputFeedback Control of an Unknown System
As the systems we control become more complex, firstprinciple modeling ...
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Simple random search provides a competitive approach to reinforcement learning
A common belief in modelfree reinforcement learning is that methods bas...
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Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law
We prove a query complexity lower bound for approximating the top r dime...
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Do CIFAR10 Classifiers Generalize to CIFAR10?
Machine learning is currently dominated by largely experimental work foc...
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Minimax Lower Bounds for H_∞Norm Estimation
The problem of estimating the H_∞norm of an LTI system from noisy input...
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Massively Parallel Hyperparameter Tuning
Modern learning models are characterized by large hyperparameter spaces....
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numpywren: serverless linear algebra
Linear algebra operations are widely used in scientific computing and ma...
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Finitetime Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
We study the sample complexity of approximate policy iteration (PI) for ...
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PostEstimation Smoothing: A Simple Baseline for Learning with Side Information
Observational data are often accompanied by natural structural indices, ...
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Meaningless comparisons lead to false optimism in medical machine learning
A new trend in medicine is the use of algorithms to analyze big datasets...
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