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GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
15 years 10 months ago
Mining breast cancer data with XCS
In this paper, we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a prima...
Faten Kharbat, Larry Bull, Mohammed Odeh
ISBI
2011
IEEE
14 years 7 months ago
Sparse Riemannian manifold clustering for HARDI segmentation
We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast thi...
Hasan Ertan Çetingül, René Vida...
TIT
2010
174views Education» more  TIT 2010»
14 years 10 months ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
PODC
2005
ACM
15 years 9 months ago
Facility location: distributed approximation
In this paper, we initiate the study of the approximability of the facility location problem in a distributed setting. In particular, we explore a trade-off between the amount of...
Thomas Moscibroda, Roger Wattenhofer
DIALM
2004
ACM
113views Algorithms» more  DIALM 2004»
15 years 9 months ago
Gathering correlated data in sensor networks
In this paper, we consider energy-efficient gathering of correlated data in sensor networks. We focus on single-input coding strategies in order to aggregate correlated data. For ...
Pascal von Rickenbach, Roger Wattenhofer