Amanote Research

Amanote Research

    RegisterSign In

The Maximum Likelihood Approach to Voting on Social Networks

doi 10.1109/allerton.2013.6736702
Full Text
Open PDF
Abstract

Available in full text

Date

October 1, 2013

Authors
Vincent Conitzer
Publisher

IEEE


Related search

Inferring the Maximum Likelihood Hierarchy in Social Networks

2009English

Iterative Maximum Likelihood on Networks

Advances in Applied Mathematics
Applied Mathematics
2010English

Maximum Likelihood Approach

2013English

On Truth Discovery in Social Sensing: A Maximum Likelihood Estimation Approach

2012English

Algebraic Methods for Inferring Biochemical Networks: A Maximum Likelihood Approach

Computational Biology and Chemistry
BiochemistryComputational MathematicsStructural BiologyOrganic Chemistry
2009English

Maximum Echo-State-Likelihood Networks for Emotion Recognition

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2010English

The Finite Population Bootstrap - From the Maximum Likelihood to the Horvitz-Thompson Approach

Austrian Journal of Statistics
UncertaintyApplied MathematicsStatisticsProbability
2014English

An Alternative to Maximum Likelihood Based on Spacings

Econometric Theory
EconomicsEconometricsSocial Sciences
2005English

Robust Maximum Likelihood Training of Heteroscedastic Probabilistic Neural Networks

Neural Networks
Artificial IntelligenceCognitive Neuroscience
1998English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy