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» Feature selection for linear support vector machines
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ML
2008
ACM
248views Machine Learning» more  ML 2008»
14 years 11 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»
15 years 5 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
15 years 1 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»
15 years 5 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»
14 years 10 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