User profiles for Yoav Freund
 | Yoav FreundUCSD Verified email at eng.ucsd.edu Cited by 75641 |
[PDF][PDF] Experiments with a new boosting algorithm
Y Freund, RE Schapire - icml, 1996 - Citeseer
In an earlier paper [9], we introduced a new “boosting” algorithm called AdaBoost which,
theoretically, can be used to significantly reduce the error of any learning algorithm that …
theoretically, can be used to significantly reduce the error of any learning algorithm that …
A decision-theoretic generalization of on-line learning and an application to boosting
Y Freund, RE Schapire - Journal of computer and system sciences, 1997 - Elsevier
In the first part of the paper we consider the problem of dynamically apportioning resources
among a set of options in a worst-case on-line framework. The model we study can be …
among a set of options in a worst-case on-line framework. The model we study can be …
[PDF][PDF] A short introduction to boosting
Boosting is a general method for improving the accuracy of any given learning algorithm.
This short overview paper introduces the boosting algorithm AdaBoost, and explains the …
This short overview paper introduces the boosting algorithm AdaBoost, and explains the …
A desicion-theoretic generalization of on-line learning and an application to boosting
Y Freund, RE Schapire - European conference on computational learning …, 1995 - Springer
We consider the problem of dynamically apportioning resources among a set of options in a
worst-case on-line framework. The model we study can be interpreted as a broad, abstract …
worst-case on-line framework. The model we study can be interpreted as a broad, abstract …
Boosting a weak learning algorithm by majority
Y Freund - Information and computation, 1995 - Elsevier
We present an algorithm for improving the accuracy of algorithms for learning binary concepts.
The improvement is achieved by combining a large number of hypotheses, each of which …
The improvement is achieved by combining a large number of hypotheses, each of which …
[PDF][PDF] An efficient boosting algorithm for combining preferences
Y Freund, R Iyer, RE Schapire, Y Singer - Journal of machine learning …, 2003 - jmlr.org
We study the problem of learning to accurately rank a set of objects by combining a given
collection of ranking or preference functions. This problem of combining preferences arises in …
collection of ranking or preference functions. This problem of combining preferences arises in …
Boosting the margin: A new explanation for the effectiveness of voting methods
One of the surprising recurring phenomena observed in experiments with boosting is that
the test error of the generated classifier usually does not increase as its size becomes very …
the test error of the generated classifier usually does not increase as its size becomes very …
The nonstochastic multiarmed bandit problem
In the multiarmed bandit problem, a gambler must decide which arm of K nonidentical slot
machines to play in a sequence of trials so as to maximize his reward. This classical problem …
machines to play in a sequence of trials so as to maximize his reward. This classical problem …
[PDF][PDF] Large margin classification using the perceptron algorithm
Y Freund, RE Schapire - Proceedings of the eleventh annual conference …, 1998 - dl.acm.org
We introduce and analyze a new algorithm for linear classification whichcombines
Rosenblatt’sperceptron algorithm with Helmbold and Warmuth’s leave-one-out method. Like …
Rosenblatt’sperceptron algorithm with Helmbold and Warmuth’s leave-one-out method. Like …
Selective sampling using the query by committee algorithm
We analyze the “query by committee” algorithm, a method for filtering informative queries from
a random stream of inputs. We show that if the two-member committee algorithm achieves …
a random stream of inputs. We show that if the two-member committee algorithm achieves …