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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 6 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ISMAR
2009
IEEE
16 years 1 months ago
Real-time in-situ visual feedback of task performance in mixed environments for learning joint psychomotor-cognitive tasks
This paper proposes an approach to mixed environment training of manual tasks requiring concurrent use of psychomotor and cognitive skills. To train concurrent use of both skill s...
Aaron Kotranza, D. Scott Lind, Carla M. Pugh, Benj...
FOCS
2006
IEEE
16 years 13 days ago
Hardness of Learning Halfspaces with Noise
Learning an unknown halfspace (also called a perceptron) from labeled examples is one of the classic problems in machine learning. In the noise-free case, when a halfspace consist...
Venkatesan Guruswami, Prasad Raghavendra
LLL
1999
Springer
15 years 10 months ago
Learning to Lemmatise Slovene Words
Abstract. Automatic lemmatisation is a core application for many language processing tasks. In inflectionally rich languages, such as Slovene, assigning the correct lemma to each ...
Saso Dzeroski, Tomaz Erjavec
ICRA
2006
IEEE
87views Robotics» more  ICRA 2006»
16 years 12 days ago
Learning to Predict Slip for Ground Robots
— In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do t...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...