410 search results - page 19 / 82 » MILIS: Multiple Instance Learning with Instance Selection |
NIPS
2004
13 years 10 months ago
2004
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
AI
2009
Springer
14 years 3 months ago
2009
Springer
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
COLT
2010
Springer
13 years 7 months ago
2010
Springer
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
AUSAI
2004
Springer
14 years 2 months ago
2004
Springer
Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
CIKM
2008
Springer
13 years 11 months ago
2008
Springer
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the m...