Concept

Euclidean distance

Publications associées (209)

Distinct distances between points and lines

Frank de Zeeuw, Adrian Claudiu Valculescu, Shakhar Smorodinsky

We show that for m points and n lines in R-2, the number of distinct distances between the points and the lines is Omega(m(1/5)n(3/5)), as long as m(1/2)

Elsevier Science Bv2018

epsilon-Coresets for Clustering (with Outliers) in Doubling Metrics

Jian Li, Lingxiao Huang

We study the problem of constructing epsilon-coresets for the (k, z)-clustering problem in a doubling metric M(X, d). An epsilon-coreset is a weighted subset S subset of X with weight function w : S -> R->= 0, such that for any k-subset C is an element of ...

IEEE COMPUTER SOC2018

Symplectic Model-Reduction with a Weighted Inner Product

Jan Sickmann Hesthaven, Babak Maboudi Afkham

In the recent years, considerable attention has been paid to preserving structures and invariants in reduced basis methods, in order to enhance the stability and robustness of the reduced system. In the context of Hamiltonian systems, symplectic model redu ...

2018

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Sebastian Urban Stich

We present the first accelerated randomized algorithm for solving linear systems in Euclidean spaces. One essential problem of this type is the matrix inversion problem. In particular, our algorithm can be specialized to invert positive definite matrices i ...

2018

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Sebastian Urban Stich

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Testing Graph Clusterability: Algorithms and Lower Bounds

Mikhail Kapralov, Aidasadat Mousavifar, Ashish Hari Chiplunkar

We consider the problem of testing graph cluster structure: given access to a graph G = (V, E), can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph? This is a generali ...

IEEE COMPUTER SOC2018

A statistical shape model to predict the premorbid glenoid cavity

Alexandre Terrier, Alain Farron, Steve Michel Berger, Daniel Abler, Philippe Büchler

Background: This study proposes a method for inferring the premorbid glenoid shape and orientation of scapulae affected by glenohumeral osteoarthritis (OA) to inform restorative surgery. Methods: A statistical shape model (SSM) built from 64 healthy scapul ...

MOSBY-ELSEVIER2018

Algorithms For Clustering Problems

Ashkan Norouzi Fard

Clustering is a classic topic in combinatorial optimization and plays a central role in many areas, including data science and machine learning. In this thesis, we first focus on the dynamic facility location problem (i.e., the facility location problem in ...

EPFL2018

End-to-end text-dependent speaker verification using novel distance measures

Petr Motlicek, Subhadeep Dey

This paper explores novel ideas in building end-to-end deep neural network (DNN) based text-dependent speaker verification (SV) system. The baseline approach consists of mapping a variable length speech segment to a fixed dimensional speaker vector by esti ...

2018

Omnidirectional bats, point-to-plane distances, and the price of uniqueness

Martin Vetterli, Ivan Dokmanic, Miranda Krekovic

We study simultaneous localization and mapping with a device that uses reflections to measure its distance from walls. Such a device can be realized acoustically with a synchronized collocated source and receiver; it behaves like a bat with no capacity for ...

Ieee2017

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