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TIP
2010
155views more  TIP 2010»
13 years 8 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
MICCAI
2008
Springer
14 years 11 months ago
Discovering Structure in the Space of Activation Profiles in fMRI
We present a method for discovering patterns of activation observed through fMRI in experiments with multiple stimuli/tasks. We introduce an explicit parameterization for the profi...
Danial Lashkari, Ed Vul, Nancy Kanwisher, Polin...
ICPR
2008
IEEE
14 years 4 months ago
Robust indoor activity recognition via boosting
In this paper, a novel statistical indoor activity recognition algorithm is introduced. While conditional random fields (CRFs) have prominent properties to this task, no optimal ...
Masamichi Shimosaka, Taketoshi Mori, Tomomasa Sato
IJCAI
2001
13 years 11 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
ICCS
2007
Springer
14 years 4 months ago
Active Learning with Support Vector Machines for Tornado Prediction
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...