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» Learning to Identify Unexpected Instances in the Test Set
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ICPR
2006
IEEE
14 years 5 months ago
Learning Policies for Efficiently Identifying Objects of Many Classes
Viola and Jones (VJ) cascade classification methods have proven to be very successful in detecting objects belonging to a single class -- e.g., faces. This paper addresses the mor...
Ahmed M. Elgammal, Ramana Isukapalli, Russell Grei...
KDD
2002
ACM
108views Data Mining» more  KDD 2002»
14 years 4 months ago
Incremental Machine Learning to Reduce Biochemistry Lab Costs in the Search for Drug Discovery
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
George Forman
JCST
2006
128views more  JCST 2006»
13 years 4 months ago
Multi-Instance Learning from Supervised View
Abstract In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. This pa...
Zhi-Hua Zhou
FUIN
2002
132views more  FUIN 2002»
13 years 4 months ago
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
Grzegorz Góra, Arkadiusz Wojna
IJCAI
2007
13 years 5 months ago
Optimistic Active-Learning Using Mutual Information
An “active learning system” will sequentially decide which unlabeled instance to label, with the goal of efficiently gathering the information necessary to produce a good cla...
Yuhong Guo, Russell Greiner