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CADE
2006
Springer
16 years 1 months ago
Solving Sparse Linear Constraints
Linear arithmetic decision procedures form an important part of theorem provers for program verification. In most verification benchmarks, the linear arithmetic constraints are dom...
Shuvendu K. Lahiri, Madanlal Musuvathi
ICASSP
2008
IEEE
15 years 7 months ago
Subspace compressive detection for sparse signals
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler
ICDAR
2007
IEEE
15 years 7 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
ICRA
2006
IEEE
119views Robotics» more  ICRA 2006»
15 years 7 months ago
SLAM with Sparse Sensing
— Most work on the simultaneous localization and mapping (SLAM) problem assumes the frequent availability of dense information about the environment such as that provided by a la...
Kristopher R. Beevers, Wesley H. Huang
ROBOCUP
2005
Springer
164views Robotics» more  ROBOCUP 2005»
15 years 6 months ago
Laser-Based Localization with Sparse Landmarks
Abstract. Self-localization in dynamic environments is a central problem in mobile robotics and is well studied in the literature. One of the most popular methods is the Monte Carl...
Andreas Strack, Alexander Ferrein, Gerhard Lakemey...