Publications related to Clustering of heterogeneous networks with directional flows based on “Snake” similarities

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes

The structure in cortical microcircuits deviates from what would be expected in a purely random network, which has been seen as evidence of clustering. To address this issue, we sought to reproduce the nonrandom features of cortical circuits by considering ...

Soc Neuroscience2017

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

The problem of clustering in urban traffic networks has been mainly studied in static framework by considering traffic conditions at a given time. Nevertheless, it is important to underline that traffic is a strongly time-variant process and it needs to be ...

2017

Dynamic Facility Location via Exponential Clocks

Ola Nils Anders Svensson, Ashkan Norouzi Fard, Hyung Chan An

The dynamic facility location problem is a generalization of the classic facility location problem proposed by Eisenstat, Mathieu, and Schabanel to model the dynamics of evolving social/infrastructure networks. The generalization lies in that the distance ...

Association for Computing Machinery2017

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

The problem of clustering in urban traffic networks has been mainly studied in static framework by considering traffic conditions at a given time. Nevertheless, it is important to underline that traffic is a strongly time-variant process and it needs to be ...

2017

A Bi-Criteria Approximation Algorithm for k-Means

Justin Dean Ward

We consider the classical k-means clustering problem in the setting of bi-criteria approximation, in which an algorithm is allowed to output beta*k > k clusters, and must produce a clustering with cost at most alpha times the to the cost of the optimal set ...

Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik2016

Pattern-based fpga logic block and clustering algorithm

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Xifan Tang

A routing architecture for fast interconnections between Look-Up Tables (LUTs) in a group of Basic Logic Elements (BLEs), whereby a size of the group ranges from 1 to k+1, where k is the number of inputs of a LUT, and LUTs in the group are indexed from 1 t ...

2016

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We build upon recent advances in graph signal processing to propose a faster spectral clustering algorithm. Indeed, classical spectral clustering is based on the computation of the first

k

eigenvectors of the similarity matrix' Laplacian, whose computati ...

Ieee2016

Fast K-Means with Accurate Bounds

François Fleuret, James Peter Newling

We propose a novel accelerated exact

k

-means algorithm, which outperforms the current state-of-the-art low-dimensional algorithm in 18 of 22 experiments, running up to 3

\times

faster. We also propose a general improvement of existing state-of-the-art a ...

Idiap2016

Nmf-Based Blind Source Separation Using A Linear Predictive Coding Error Clustering Criterion

Xin Guo

Non-negative matrix factorization (NMF) based sound source separation involves two phases: First, the signal spectrum is decomposed into components which, in a second step, are clustered in order to obtain estimates of the source signal spectra. The major ...

Ieee2015

Decentralized clustering over adaptive networks

Ali H. Sayed, Ali Zoubir

Cooperation among agents across the network leads to better estimation accuracy. However, in many network applications the agents infer and track different models of interest in an environment where agents do not know beforehand which models are being obse ...

IEEE2015

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

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On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Dynamic Facility Location via Exponential Clocks

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

A Bi-Criteria Approximation Algorithm for k-Means

Pattern-based fpga logic block and clustering algorithm

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Fast K-Means with Accurate Bounds

Nmf-Based Blind Source Separation Using A Linear Predictive Coding Error Clustering Criterion

Decentralized clustering over adaptive networks

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Dynamic Facility Location via Exponential Clocks

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Pattern-based fpga logic block and clustering algorithm

A Bi-Criteria Approximation Algorithm for k-Means

Decentralized clustering over adaptive networks

Nmf-Based Blind Source Separation Using A Linear Predictive Coding Error Clustering Criterion

Fast K-Means with Accurate Bounds

Accelerated Spectral Clustering Using Graph Filtering of Random Signals