research
∙
06/28/2023
Finite-Sample Symmetric Mean Estimation with Fisher Information Rate
The mean of an unknown variance-σ^2 distribution f can be estimated from...
share
research
∙
02/19/2023
Accelerated Video Annotation driven by Deep Detector and Tracker
Annotating object ground truth in videos is vital for several downstream...
research
∙
02/05/2023
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors
In location estimation, we are given n samples from a known distribution...
research
∙
09/26/2022
Perception-driven Formation Control of Airships
For tracking and motion capture (MoCap) of animals in their natural habi...
research
∙
06/29/2022
Hardness and Algorithms for Robust and Sparse Optimization
We explore algorithms and limitations for sparse optimization problems s...
research
∙
06/21/2022
Sharp Constants in Uniformity Testing via the Huber Statistic
Uniformity testing is one of the most well-studied problems in property ...
research
∙
06/06/2022
Finite-Sample Maximum Likelihood Estimation of Location
We consider 1-dimensional location estimation, where we estimate a param...
research
∙
03/10/2022
Deep Residual Reinforcement Learning based Autonomous Blimp Control
Blimps are well suited to perform long-duration aerial tasks as they are...
research
∙
03/06/2022
Coresets for Data Discretization and Sine Wave Fitting
In the monitoring problem, the input is an unbounded stream P=p_1,p_2⋯ o...
research
∙
01/20/2022
AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation
In this letter, we present a novel markerless 3D human motion capture (M...
research
∙
12/14/2021
Simulating Random Walks in Random Streams
The random order graph streaming model has received significant attentio...
research
∙
10/19/2021
Factorial Lower Bounds for (Almost) Random Order Streams
In this paper we introduce and study the StreamingCycles problem, a rand...
research
∙
09/22/2021
Autonomous Blimp Control using Deep Reinforcement Learning
Aerial robot solutions are becoming ubiquitous for an increasing number ...
research
∙
08/03/2021
Robust Compressed Sensing MRI with Deep Generative Priors
The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep gen...
research
∙
06/23/2021
Fairness for Image Generation with Uncertain Sensitive Attributes
This work tackles the issue of fairness in the context of generative pro...
research
∙
06/21/2021
Instance-Optimal Compressed Sensing via Posterior Sampling
We characterize the measurement complexity of compressed sensing of sign...
research
∙
06/01/2021
Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing
In group testing, the goal is to identify a subset of defective items wi...
research
∙
05/24/2021
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 ...
research
∙
05/19/2021
L1 Regression with Lewis Weights Subsampling
We consider the problem of finding an approximate solution to ℓ_1 regres...
research
∙
03/03/2021
Linear Bandit Algorithms with Sublinear Time Complexity
We propose to accelerate existing linear bandit algorithms to achieve pe...
research
∙
12/31/2020
Simulation and Control of Deformable Autonomous Airships in Turbulent Wind
Abstract. Fixed wing and multirotor UAVs are common in the field of robo...
research
∙
11/09/2020
Near-Optimal Learning of Tree-Structured Distributions by Chow-Liu
We provide finite sample guarantees for the classical Chow-Liu algorithm...
research
∙
09/14/2020
Optimal Testing of Discrete Distributions with High Probability
We study the problem of testing discrete distributions with a focus on t...
research
∙
06/18/2020
A Fast Binary Splitting Approach to Non-Adaptive Group Testing
In this paper, we consider the problem of noiseless non-adaptive group t...
research
∙
12/06/2019
Lower Bounds for Compressed Sensing with Generative Models
The goal of compressed sensing is to learn a structured signal x from a ...
research
∙
11/19/2019
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
We study high-dimensional sparse estimation tasks in a robust setting wh...
research
∙
05/07/2019
Exponential Separations Between Turnstile Streaming and Linear Sketching
Almost every known turnstile streaming algorithm is implementable as a l...
research
∙
04/30/2019
Estimating the Frequency of a Clustered Signal
We consider the problem of locating a signal whose frequencies are "off ...
research
∙
01/23/2019
Active Perception based Formation Control for Multiple Aerial Vehicles
Autonomous motion capture (mocap) systems for outdoor scenarios involvin...
research
∙
11/15/2018
Adversarial Examples from Cryptographic Pseudo-Random Generators
In our recent work (Bubeck, Price, Razenshteyn, arXiv:1805.10204) we arg...
research
∙
09/21/2018
Compressed Sensing with Adversarial Sparse Noise via L1 Regression
We present a simple and effective algorithm for the problem of sparse ro...
research
∙
08/15/2018
The Sketching Complexity of Graph and Hypergraph Counting
Subgraph counting is a fundamental primitive in graph processing, with a...
research
∙
07/23/2018
Batch Sparse Recovery, or How to Leverage the Average Sparsity
We introduce a batch version of sparse recovery, where the goal is to re...
research
∙
06/17/2018
Compressed Sensing with Deep Image Prior and Learned Regularization
We propose a novel method for compressed sensing recovery using untraine...
research
∙
05/25/2018
Adversarial examples from computational constraints
Why are classifiers in high dimension vulnerable to "adversarial" pertur...
research
∙
02/05/2018
Deep Neural Network-based Cooperative Visual Tracking through Multiple Micro Aerial Vehicles
Multi-camera full-body pose capture of humans and animals in outdoor env...
research
∙
12/25/2017
Stochastic Multi-armed Bandits in Constant Space
We consider the stochastic bandit problem in the sublinear space setting...
research
∙
11/27/2017
Condition number-free query and active learning of linear families
We consider the problem of learning a function from samples with ℓ_2-bou...
research
∙
03/09/2017
Compressed Sensing using Generative Models
The goal of compressed sensing is to estimate a vector from an underdete...
research
∙
11/02/2016
Extensions and Limitations of the Neural GPU
The Neural GPU is a recent model that can learn algorithms such as multi...
research
∙
04/19/2014
