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IJCAI
2001
13 years 10 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
ICASSP
2008
IEEE
14 years 3 months ago
Multi-feature vector flow for active contour tracking
In order to achieve both fast tracking and accurate object extraction, we present in this paper an original real-time active contour method, incorporating different feature maps i...
Joanna I. Olszewska, Christophe De Vleeschouwer, B...
ESA
2008
Springer
95views Algorithms» more  ESA 2008»
13 years 10 months ago
Speed Scaling Functions for Flow Time Scheduling Based on Active Job Count
Abstract. We study online scheduling to minimize flow time plus energy usage in the dynamic speed scaling model. We devise new speed scaling functions that depend on the number of ...
Tak Wah Lam, Lap-Kei Lee, Isaac Kar-Keung To, Prud...
TIP
2010
155views more  TIP 2010»
13 years 7 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
BIOSYSTEMS
2007
56views more  BIOSYSTEMS 2007»
13 years 9 months ago
Determination of the fraction of active inputs required by a neuron to fire
What fraction of the inputs to a neuron in the primary visual cortex (V1) need to be active for that neuron to reach its firing threshold? The paper describes a numerical method f...
Guido Bugmann