Robert Schapire

(5 articles)
Empirical Risk Minimization
1974

Empirical Risk Minimization

A foundational principle in statistics and ML (Machine Learning), focused on minimizing the average of the loss function over a sample dataset.

Generality: 814

Boosting
1989

Boosting

ML ensemble technique that combines multiple weak learners to form a strong learner, aiming to improve the accuracy of predictions.

Generality: 800

Ensamble Algorithm
1992

Ensamble Algorithm

Combines multiple machine learning models to improve overall performance by reducing bias, variance, or noise.

Generality: 860

Ensemble Methods
1996

Ensemble Methods

ML technique where multiple models are trained and used collectively to solve a problem.

Generality: 860

Ensemble Learning
1996

Ensemble Learning

ML paradigm where multiple models (often called weak learners) are trained to solve the same problem and combined to improve the accuracy of predictions.

Generality: 795