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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 7 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
ECTEL
2007
Springer
16 years 1 months ago
ALOE - A Socially Aware Learning Resource and Metadata Hub
The changing nature of e-Learning, the Web, and its users that can be observed in the last years results in a need for new approaches and technologies to fully exploit the existing...
Martin Memmel, Rafael Schirru
SIGECOM
2010
ACM
149views ECommerce» more  SIGECOM 2010»
16 years 1 days ago
A new understanding of prediction markets via no-regret learning
We explore the striking mathematical connections that exist between market scoring rules, cost function based prediction markets, and no-regret learning. We first show that any c...
Yiling Chen, Jennifer Wortman Vaughan
ICML
1999
IEEE
15 years 11 months ago
Learning Hierarchical Performance Knowledge by Observation
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Michael van Lent, John E. Laird