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We present a convolutional network that is equivariant to rigid body motions. The model uses scalar-, vector-, and tensor fields over 3D Euclidean space to represent data, and equivariant convolutions to map between such representations. These SE(3)-equiva ...
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018
We generalize the ham sandwich theorem to d +1 measures on R-d as follows. Let mu(1), mu(2),..., mu(d+1) be absolutely continuous finite Borel measures on R-d. Let omega(i) = mu(i) (R-d) for i is an element of [d + 1], omega = min{omega(i) : i is an elemen ...
Elsevier Science Bv2018
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A slab (or plank) is the part of the d-dimensional Euclidean space that lies between two parallel hyperplanes. The distance between the these hyperplanes is called the width of the slab. It is conjectured that the members of any infinite family of slabs wi ...
The relationship between collapsibility and confounding has been subject to an extensive and ongoing discussion in the methodological literature. We discuss two subtly different definitions of collapsibility, and show that by considering causal effect meas ...
We obtain quantitative bounds on the mixing properties of the Hamiltonian Monte Carlo (HMC) algorithm with target distribution in d-dimensional Euclidean space, showing that HMC mixes quickly whenever the target log-distribution is strongly concave and has ...
We present new techniques to analyze natural local search algorithms for several variants of the max-sum diversification problem which, in its most basic form, is as follows: given an n-point set X subset of R-d and an integer k, select k points in X so th ...
Prior studies have examined the relationship between organizational ethical climates and an array of work-related attitudes and behaviors. However, current research is hampered by the lack of knowledge on how ethical climates relate to organizational outco ...
This report explains all theoretical and practical aspects of a 2D room re- construction algorithm based on euclidean geometry. Detailed theoretical explanations about the procedure are given in the first part. In the second part, a precise description of ...
We present a general theory of Group equivariant Convolutional Neural Networks (G-CNNs) on homogeneous spaces such as Euclidean space and the sphere. Feature maps in these networks represent fields on a homogeneous base space, and layers are equivariant ma ...
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019
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Asynchronous video interviews (AVIs) are increasingly used by organizations in their hiring process. In this mode of interviewing, the applicants are asked to record their responses to predefined interview questions using a webcam via an online platform. A ...
