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ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
15 years 12 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
ICA
2007
Springer
15 years 12 months ago
Sparse Component Analysis in Presence of Noise Using an Iterative EM-MAP Algorithm
Abstract. In this paper, a new algorithm for source recovery in underdetermined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented i...
Hadi Zayyani, Massoud Babaie-Zadeh, G. Hosein Mohi...
ISQED
2000
IEEE
117views Hardware» more  ISQED 2000»
15 years 10 months ago
Realistic Worst-Case Modeling by Performance Level Principal Component Analysis
A new algorithm to determine the number and value of realistic worst-case models for the performance of module library components is presented in this paper. The proposed algorith...
Alessandra Nardi, Andrea Neviani, Carlo Guardiani
ICDCS
2005
IEEE
15 years 11 months ago
Optimal Component Composition for Scalable Stream Processing
Stream processing has become increasingly important with emergence of stream applications such as audio/video surveillance, stock price tracing, and sensor data analysis. A challe...
Xiaohui Gu, Philip S. Yu, Klara Nahrstedt
ISCAS
2008
IEEE
169views Hardware» more  ISCAS 2008»
16 years 7 days ago
Sigma-delta learning for super-resolution independent component analysis
— Many source separation algorithms fail to deliver robust performance in presence of artifacts introduced by cross-channel redundancy, non-homogeneous mixing and highdimensional...
Amin Fazel, Shantanu Chakrabartty