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» Feature selection for linear support vector machines
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ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 7 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
MM
2003
ACM
111views Multimedia» more  MM 2003»
14 years 1 months ago
A robust dissolve detector by support vector machine
In this paper, we propose a novel approach for the robust detection and classification of dissolve sequences in videos. Our approach is based on the multi-resolution representati...
Chong-Wah Ngo
ICCV
2007
IEEE
13 years 9 months ago
Combined Support Vector Machines and Hidden Markov Models for Modeling Facial Action Temporal Dynamics
The analysis of facial expression temporal dynamics is of great importance for many real-world applications. Being able to automatically analyse facial muscle actions (Action Units...
Michel François Valstar, Maja Pantic
ADMA
2005
Springer
149views Data Mining» more  ADMA 2005»
14 years 1 months ago
A New Support Vector Machine for Data Mining
Abstract. This paper proposes a new support vector machine (SVM) with a robust loss function for data mining. Its dual optimal formation is also constructed. A gradient based algor...
Haoran Zhang, Xiaodong Wang, Changjiang Zhang, Xiu...
ML
2010
ACM
181views Machine Learning» more  ML 2010»
13 years 6 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor