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» Learning of Boolean Functions Using Support Vector Machines
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ECCC
2010
124views more  ECCC 2010»
13 years 9 months ago
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio
ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
13 years 7 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...
TNN
2008
178views more  TNN 2008»
13 years 9 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
ICALT
2008
IEEE
14 years 3 months ago
Learning Application Suite Creating and Playing SCORM Compatible Web and Computer Based Training
In the process of developing Web Based Training (WBT) applications, the Sharable Content Object Reference Model (SCORM) has become the most common eLearning standard making it pos...
Marco Nordmann, Jens Neumann
ICASSP
2010
IEEE
13 years 7 months ago
A comparison of approaches for modeling prosodic features in speaker recognition
Prosodic information has been successfully used for speaker recognition for more than a decade. The best-performing prosodic system to date has been one based on features extracte...
Luciana Ferrer, Nicolas Scheffer, Elizabeth Shribe...