ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
In this work, we present a new bottom-up algorithmfor decision tree pruning that is very e cient requiring only a single pass through the given tree, and prove a strong performanc...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
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 aris...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
Relational reinforcement learning (RRL) is both a young and an old eld. In this paper, we trace the history of the eld to related disciplines, outline some current work and promis...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
Predicting items a user would like on the basis of other users' ratings for these items has become a well-established strategy adopted by many recommendation services on the ...