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» On sparse signal representations
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IPSN
2009
Springer
16 years 1 months ago
Near-optimal Bayesian localization via incoherence and sparsity
This paper exploits recent developments in sparse approximation and compressive sensing to efficiently perform localization in a sensor network. We introduce a Bayesian framework...
Volkan Cevher, Petros Boufounos, Richard G. Barani...
NIPS
2007
15 years 8 months ago
Compressed Regression
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
NIPS
1992
15 years 7 months ago
Filter Selection Model for Generating Visual Motion Signals
Neurons in area MT of primate visual cortex encode the velocity of moving objects. We present a model of how MT cells aggregate responses from V1 to form such a velocity represent...
Steven J. Nowlan, Terrence J. Sejnowski
CISS
2011
IEEE
14 years 10 months ago
Stable manifold embeddings with operators satisfying the Restricted Isometry Property
—Signals of interests can often be thought to come from a low dimensional signal model. The exploitation of this fact has led to many recent interesting advances in signal proces...
Han Lun Yap, Michael B. Wakin, Christopher J. Roze...
ECCV
2006
Springer
16 years 8 months ago
Sparse Flexible Models of Local Features
Abstract. In recent years there has been growing interest in recognition models using local image features for applications ranging from long range motion matching to object class ...
Gustavo Carneiro, David Lowe