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ISMIS
2000
Springer
15 years 8 months ago
Prediction of Ordinal Classes Using Regression Trees
This paper is devoted to the problem of learning to predict ordinal (i.e., ordered discrete) classes using classification and regression trees. We start with S-CART, a tree inducti...
Stefan Kramer, Gerhard Widmer, Bernhard Pfahringer...
SIAMCOMP
2011
14 years 11 months ago
Self-Improving Algorithms
We investigate ways in which an algorithm can improve its expected performance by fine-tuning itself automatically with respect to an arbitrary, unknown input distribution. We gi...
Nir Ailon, Bernard Chazelle, Kenneth L. Clarkson, ...
ICML
2008
IEEE
16 years 5 months ago
Learning all optimal policies with multiple criteria
We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal policies for all linear pref...
Leon Barrett, Srini Narayanan
ICML
2010
IEEE
15 years 2 months ago
Learning optimally diverse rankings over large document collections
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
AIPS
1994
15 years 5 months ago
A Planner with Quality Goal and Its Speed-up Learning for Optimization Problem
Aimsof traditional planners had beenlimited to finding a sequenceof operators rather than finding an optimal or neax-optimalfinal state. Consequent]y, the performanceimprovementsy...
Masahiko Iwamoto