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ECML
2004
Springer
15 years 10 months ago
A Boosting Approach to Multiple Instance Learning
In this paper we present a boosting approach to multiple instance learning. As weak hypotheses we use balls (with respect to various metrics) centered at instances of positive bags...
Peter Auer, Ronald Ortner
PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
15 years 11 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone
PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
15 years 9 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...
KDD
1994
ACM
98views Data Mining» more  KDD 1994»
15 years 9 months ago
Rule Induction for Semantic Query Optimization
Semantic query optimization can dramatically speed up database query answering by knowledge intensive reformulation. But the problem of how to learn required semantic rules has no...
Chun-Nan Hsu, Craig A. Knoblock
151
Voted
KDD
1995
ACM
133views Data Mining» more  KDD 1995»
15 years 8 months ago
Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
In the wrapperapproachto feature subset selection, a searchfor an optimalset of features is madeusingthe induction algorithm as a black box. Theestimated future performanceof the ...
Ron Kohavi, Dan Sommerfield