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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
14 years 7 months ago
Active Learning from Multiple Noisy Labelers with Varied Costs
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Yaling Zheng, Stephen D. Scott, Kun Deng
ICML
2010
IEEE
14 years 10 months ago
Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
Daniel J. Lizotte, Michael H. Bowling, Susan A. Mu...
JMLR
2006
156views more  JMLR 2006»
14 years 9 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ISVC
2010
Springer
14 years 8 months ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
Karthik Sankaranarayanan, James W. Davis
SIGMOD
2008
ACM
145views Database» more  SIGMOD 2008»
15 years 10 months ago
Optimizing complex queries with multiple relation instances
Today's query processing engines do not take advantage of the multiple occurrences of a relation in a query to improve performance. Instead, each instance is treated as a dis...
Yu Cao, Gopal C. Das, Chee Yong Chan, Kian-Lee Tan