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» Learning of Boolean Functions Using Support Vector Machines
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ICML
2010
IEEE
13 years 10 months ago
Multi-Class Pegasos on a Budget
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Zhuang Wang, Koby Crammer, Slobodan Vucetic
FLAIRS
2000
13 years 10 months ago
A Multiagent Architecture to Support Distance Learning Personalization on the Web
This article presents the description of the objectives, the structure and the functionality of an interactive system intended to focus the teaching on the performanceof the stude...
Jesus Boticario, Elena Gaudioso
ICML
2009
IEEE
14 years 10 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
ICMI
2007
Springer
160views Biometrics» more  ICMI 2007»
14 years 3 months ago
Using the influence model to recognize functional roles in meetings
In this paper, an influence model is used to recognize functional roles played during meetings. Previous works on the same corpus demonstrated a high recognition accuracy using SV...
Wen Dong, Bruno Lepri, Alessandro Cappelletti, Ale...
ICCS
2007
Springer
14 years 29 days ago
Efficient Measurement of the Eye Blinking by Using Decision Function for Intelligent Vehicles
In this paper, we propose an efficient measurement of the eye blinking for drowsy driver detection system that is one of the driver safety systems for the intelligent vehicle. Howe...
Ilkwon Park, Jung-Ho Ahn, Hyeran Byun