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ALT
2009
Springer
14 years 7 months ago
Average-Case Active Learning with Costs
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Andrew Guillory, Jeff A. Bilmes
ALT
2006
Springer
14 years 7 months ago
Active Learning in the Non-realizable Case
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
Matti Kääriäinen
IUI
2010
ACM
14 years 7 months ago
Towards maximizing the accuracy of human-labeled sensor data
We present two studies that evaluate the accuracy of human responses to an intelligent agent’s data classification questions. Prior work has shown that agents can elicit accurat...
Stephanie Rosenthal, Anind K. Dey
TKDE
2010
182views more  TKDE 2010»
13 years 8 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
ICML
2004
IEEE
14 years 11 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...