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ICML
2009
IEEE
14 years 9 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
ISMIS
2005
Springer
14 years 1 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
FLAIRS
2007
13 years 10 months ago
Learning Paraphrases from WNS Corpora
Paraphrase detection can be seen as the task of aligning sentences that convey the same information but yet are written in different forms. Such resources are important to automat...
João Cordeiro, Gaël Dias, Pavel Brazdi...
NCA
2007
IEEE
13 years 8 months ago
A data reduction approach for resolving the imbalanced data issue in functional genomics
Learning from imbalanced data occurs frequently in many machine learning applications. One positive example to thousands of negative instances is common in scientific applications...
Kihoon Yoon, Stephen Kwek
ICML
2004
IEEE
14 years 9 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng