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» Co-Tracking Using Semi-Supervised Support Vector Machines
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AAAI
2006
15 years 7 months ago
Kernel Methods for Word Sense Disambiguation and Acronym Expansion
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
IMECS
2007
15 years 7 months ago
Investigation for Designing of Context-Aware Recommendation System Using SVM
Abstract Previously, we have proposed two recommendation systems, the Context-aware Information Filtering (C-IF) and Context-aware Collaborative Filtering (C-CF), both of which ar...
Kenta Oku, Shinsuke Nakajima, Jun Miyazaki, Shunsu...
ICASSP
2011
IEEE
14 years 10 months ago
A learning-based approach to explosives detection using Multi-Energy X-Ray Computed Tomography
In this paper we consider the task of classifying materials into explosives and non-explosives according to features obtainable from Multi-Energy X-ray Computed Tomography (MECT) ...
Limor Eger, Synho Do, Prakash Ishwar, W. Clem Karl...
SAC
2006
ACM
16 years 8 days ago
Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
Hwanjo Yu, Xiaoqian Jiang, Jaideep Vaidya
KAIS
2006
111views more  KAIS 2006»
15 years 6 months ago
Real-time classification of variable length multi-attribute motions
Multi-attribute motion data can be generated in many applications/ devices, such as motion capture devices and animations. It can have dozens of attributes, thousands of rows, and ...
Chuanjun Li, Latifur Khan, Balakrishnan Prabhakara...