Daniel Keren
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View article: A practical, fast method for solving sum-of-squares problems for very large polynomials
A practical, fast method for solving sum-of-squares problems for very large polynomials Open
Sum of squares (SOS) optimization is a powerful technique for solving problems where the positivity of a polynomials must be enforced. The common approach to solve an SOS problem is by relaxation to a Semidefinite Program (SDP). The main a…
View article: Geometric Covering using Random Fields
Geometric Covering using Random Fields Open
A set of vectors $S \subseteq \mathbb{R}^d$ is $(k_1,\varepsilon)$-clusterable if there are $k_1$ balls of radius $\varepsilon$ that cover $S$. A set of vectors $S \subseteq \mathbb{R}^d$ is $(k_2,δ)$-far from being clusterable if there ar…
View article: A Fast and Reliable Solution to PnP, Using Polynomial Homogeneity and a Theorem of Hilbert
A Fast and Reliable Solution to PnP, Using Polynomial Homogeneity and a Theorem of Hilbert Open
One of the most-extensively studied problems in three-dimensional Computer Vision is “Perspective-n-Point” (PnP), which concerns estimating the pose of a calibrated camera, given a set of 3D points in the world and their corresponding 2D p…
View article: Communication Efficient Algorithms for Bounding and Approximating the Empirical Entropy in Distributed Systems
Communication Efficient Algorithms for Bounding and Approximating the Empirical Entropy in Distributed Systems Open
The empirical entropy is a key statistical measure of data frequency vectors, enabling one to estimate how diverse the data are. From the computational point of view, it is important to quickly compute, approximate, or bound the entropy. I…
View article: The Non-Tightness of a Convex Relaxation to Rotation Recovery
The Non-Tightness of a Convex Relaxation to Rotation Recovery Open
We study the Perspective-n-Point (PNP) problem, which is fundamental in 3D vision, for the recovery of camera translation and rotation. A common solution applies polynomial sum-of-squares (SOS) relaxation techniques via semidefinite progra…
View article: Adaptive Communication Bounds for Distributed Online Learning
Adaptive Communication Bounds for Distributed Online Learning Open
We consider distributed online learning protocols that control the exchange of information between local learners in a round-based learning scenario. The learning performance of such a protocol is intuitively optimal if approximately the s…