
Fairness for Image Generation with Uncertain Sensitive Attributes
This work tackles the issue of fairness in the context of generative pro...
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InstanceOptimal Compressed Sensing via Posterior Sampling
We characterize the measurement complexity of compressed sensing of sign...
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Fast Splitting Algorithms for SparsityConstrained and Noisy Group Testing
In group testing, the goal is to identify a subset of defective items wi...
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A Simple Proof of a New Set Disjointness with Applications to Data Streams
The multiplayer promise set disjointness is one of the most widely used ...
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L1 Regression with Lewis Weights Subsampling
We consider the problem of finding an approximate solution to ℓ_1 regres...
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Linear Bandit Algorithms with Sublinear Time Complexity
We propose to accelerate existing linear bandit algorithms to achieve pe...
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Simulation and Control of Deformable Autonomous Airships in Turbulent Wind
Abstract. Fixed wing and multirotor UAVs are common in the field of robo...
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NearOptimal Learning of TreeStructured Distributions by ChowLiu
We provide finite sample guarantees for the classical ChowLiu algorithm...
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Optimal Testing of Discrete Distributions with High Probability
We study the problem of testing discrete distributions with a focus on t...
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A Fast Binary Splitting Approach to NonAdaptive Group Testing
In this paper, we consider the problem of noiseless nonadaptive group t...
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Lower Bounds for Compressed Sensing with Generative Models
The goal of compressed sensing is to learn a structured signal x from a ...
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OutlierRobust HighDimensional Sparse Estimation via Iterative Filtering
We study highdimensional sparse estimation tasks in a robust setting wh...
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Exponential Separations Between Turnstile Streaming and Linear Sketching
Almost every known turnstile streaming algorithm is implementable as a l...
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Estimating the Frequency of a Clustered Signal
We consider the problem of locating a signal whose frequencies are "off ...
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Active Perception based Formation Control for Multiple Aerial Vehicles
Autonomous motion capture (mocap) systems for outdoor scenarios involvin...
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Adversarial Examples from Cryptographic PseudoRandom Generators
In our recent work (Bubeck, Price, Razenshteyn, arXiv:1805.10204) we arg...
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Compressed Sensing with Adversarial Sparse Noise via L1 Regression
We present a simple and effective algorithm for the problem of sparse ro...
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The Sketching Complexity of Graph and Hypergraph Counting
Subgraph counting is a fundamental primitive in graph processing, with a...
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Batch Sparse Recovery, or How to Leverage the Average Sparsity
We introduce a batch version of sparse recovery, where the goal is to re...
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Compressed Sensing with Deep Image Prior and Learned Regularization
We propose a novel method for compressed sensing recovery using untraine...
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Adversarial examples from computational constraints
Why are classifiers in high dimension vulnerable to "adversarial" pertur...
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Deep Neural Networkbased Cooperative Visual Tracking through Multiple Micro Aerial Vehicles
Multicamera fullbody pose capture of humans and animals in outdoor env...
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Stochastic Multiarmed Bandits in Constant Space
We consider the stochastic bandit problem in the sublinear space setting...
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Condition numberfree query and active learning of linear families
We consider the problem of learning a function from samples with ℓ_2bou...
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Compressed Sensing using Generative Models
The goal of compressed sensing is to estimate a vector from an underdete...
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Extensions and Limitations of the Neural GPU
The Neural GPU is a recent model that can learn algorithms such as multi...
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Tight bounds for learning a mixture of two gaussians
We consider the problem of identifying the parameters of an unknown mixt...
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Eric Price
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