The mean of an unknown variance-σ^2 distribution f can be estimated
from...
Annotating object ground truth in videos is vital for several downstream...
In location estimation, we are given n samples from a known distribution...
For tracking and motion capture (MoCap) of animals in their natural habi...
We explore algorithms and limitations for sparse optimization problems s...
Uniformity testing is one of the most well-studied problems in property
...
We consider 1-dimensional location estimation, where we estimate a param...
Blimps are well suited to perform long-duration aerial tasks as they are...
In the monitoring problem, the input is an unbounded stream
P=p_1,p_2⋯ o...
In this letter, we present a novel markerless 3D human motion capture (M...
The random order graph streaming model has received significant attentio...
In this paper we introduce and study the StreamingCycles problem, a
rand...
Aerial robot solutions are becoming ubiquitous for an increasing number ...
The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep
gen...
This work tackles the issue of fairness in the context of generative
pro...
We characterize the measurement complexity of compressed sensing of sign...
In group testing, the goal is to identify a subset of defective items wi...
The multiplayer promise set disjointness is one of the most widely used
...
We consider the problem of finding an approximate solution to ℓ_1
regres...
We propose to accelerate existing linear bandit algorithms to achieve
pe...
Abstract. Fixed wing and multirotor UAVs are common in the field of robo...
We provide finite sample guarantees for the classical Chow-Liu algorithm...
We study the problem of testing discrete distributions with a focus on t...
In this paper, we consider the problem of noiseless non-adaptive group
t...
The goal of compressed sensing is to learn a structured signal x from a
...
We study high-dimensional sparse estimation tasks in a robust setting wh...
Almost every known turnstile streaming algorithm is implementable as a l...
We consider the problem of locating a signal whose frequencies are "off ...
Autonomous motion capture (mocap) systems for outdoor scenarios involvin...
In our recent work (Bubeck, Price, Razenshteyn, arXiv:1805.10204) we arg...
We present a simple and effective algorithm for the problem of sparse
ro...
Subgraph counting is a fundamental primitive in graph processing, with
a...
We introduce a batch version of sparse recovery, where the goal is to
re...
We propose a novel method for compressed sensing recovery using untraine...
Why are classifiers in high dimension vulnerable to "adversarial"
pertur...
Multi-camera full-body pose capture of humans and animals in outdoor
env...
We consider the stochastic bandit problem in the sublinear space setting...
We consider the problem of learning a function from samples with
ℓ_2-bou...
The goal of compressed sensing is to estimate a vector from an
underdete...
The Neural GPU is a recent model that can learn algorithms such as
multi...
We consider the problem of identifying the parameters of an unknown mixt...