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» Minimax Bounds for Active Learning
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IUI
2009
ACM
14 years 4 months ago
Detecting and correcting user activity switches: algorithms and interfaces
The TaskTracer system allows knowledge workers to define a set of activities that characterize their desktop work. It then associates with each user-defined activity the set of ...
Jianqiang Shen, Jed Irvine, Xinlong Bao, Michael G...
CORR
2012
Springer
198views Education» more  CORR 2012»
12 years 3 months ago
Lipschitz Parametrization of Probabilistic Graphical Models
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the ￿p-norm of the parameters. We discuss several implications ...
Jean Honorio
CCS
2008
ACM
13 years 9 months ago
Open problems in the security of learning
Machine learning has become a valuable tool for detecting and preventing malicious activity. However, as more applications employ machine learning techniques in adversarial decisi...
Marco Barreno, Peter L. Bartlett, Fuching Jack Chi...
CVPR
2009
IEEE
15 years 2 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
EUROCOLT
1997
Springer
13 years 11 months ago
Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
Pascal Koiran, Eduardo D. Sontag