ECML
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
CSFW
2004
IEEE
13 years 8 months ago
2004
IEEE
Intrusion Detection Systems (IDSs) have become an important part of operational computer security. They are the last line of defense against malicious hackers and help detect ongo...
COLT
2007
Springer
13 years 10 months ago
2007
Springer
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
We compare the practical performance of several recently proposed algorithms for active learning in the online classification setting. We consider two active learning algorithms (...