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LVA 2012 : International Conference on Latent Variable Analysis and Signal Separation (formerly the International Conference on Independent Component Analysis and Signal Separation) | |||||||||
Link: http://events.ortra.com/lva/ | |||||||||
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Call For Papers | |||||||||
LVA ICA 2012
The 10th International Conference on Latent Variable Analysis and Source Separation, LVA/ICA 2012, will be held in Tel-Aviv, Israel on March 12-15, 2012, at the Sheraton Tel-Aviv Hotel & Towers. The series began under the title of Independent Component Analysis (ICA) workshops (held approximately every 18 months), and has attracted hundreds of participants over the years, continuously broadening its horizons. Starting with the fundamentals of ICA and Blind Source Separation (BSS) in the late 1990s and early 2000s, the theme of the series has gradually expanded to include additional forms and models of general mixtures of latent variables – and was therefore re-titled Latent Variable Analysis (LVA) for the recent LVA/ICA conference in St. Malo (France) in 2010, keeping the acronym ICA as well (at least for a while), for reference to its roots and origins. Prospective authors are invited to submit original papers in all areas related to latent variable analysis, independent component analysis and signal separation, including but not limited to: -Theory: statistical and probabilistic models; detection, estimation and performance criteria and bounds; causality measures; flat, hierarchical and dynamic structures; sparsity-promoting methods; learning theory; optimization tools; -Models: latent variables modeling as parameters, vectors or signals, discrete or continuous; probabilistic or structural modeling; time-varying, memoryless, convolutive, noisy, noiseless, under- and over-complete; -Algorithms: estimation, separation, identification, detection, blind and semi-blind methods, non-negative matrix factorization, tensor decomposition, adaptive and recursive estimation; features selection; time-frequency and wavelets based analysis; complexity analysis; -Applications: speech and audio separation, recognition, dereverberation and denoising; auditory scene analysis; image segmentation, separation, fusion, classification, texture analysis; biomedical signal analysis, imaging, genomic data analysis, brain-computer interface; -Emerging related topics: social networks; data-mining; artificial intelligence; sparse coding; objective and subjective performance evaluation. |
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