Skip to search formSkip to main contentSkip to account menu

Empirical risk minimization

Known as: ERM 
Empirical risk minimization (ERM) is a principle in statistical learning theory which defines a family of learning algorithms and is used to give… 
Wikipedia (opens in a new tab)

Related topics

Related topics

19 relations
Gradient boostingHinge lossLinear classifierLoss function

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Differentially Private Empirical Risk Minimization with Input Perturbation
We propose a novel framework for the differentially private ERM, input perturbation. Existing differentially private ERM… 
Highly Cited
2014
Highly Cited
2014
Private Empirical Risk Minimization Beyond the Worst Case: The Effect of the Constraint Set Geometry
Empirical Risk Minimization (ERM) is a standard technique in machine learning, where a model is selected by minimizing a loss… 
Highly Cited
2014
Highly Cited
2014
Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis
Highly Cited
2013
Highly Cited
2013
On first-order algorithms for l1/nuclear norm minimization
In the past decade, problems related to l1/nuclear norm minimization have attracted much attention in the signal processing… 
Highly Cited
2011
Highly Cited
2011
SVR with hybrid chaotic genetic algorithms for tourism demand forecasting
Highly Cited
2010
Highly Cited
2010
Empirical relationships describing benthic impacts of salmon aquaculture
Benthic organic enrichment due to sedimentation of waste feed and fecal matter released from salmon and other marine finfish… 
Highly Cited
2009
Highly Cited
2009
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for… 
Highly Cited
1998
Highly Cited
1998
Hedging Foreign Currency Portfolios
Highly Cited
1995
Highly Cited
1995
Nonparametric estimation via empirical risk minimization
A general notion of universal consistency of nonparametric estimators is introduced that applies to regression estimation… 
Highly Cited
1988
Highly Cited
1988
Multi-level logic minimization using implicit don't cares
An approach is described for the minimization of multilevel logic circuits. A multilevel representation of a block of… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)