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ICASSP
2008
IEEE
14 years 4 months ago
Finding needles in noisy haystacks
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles ...
Rui M. Castro, Jarvis Haupt, Robert Nowak, Gil M. ...
MASCOTS
2010
13 years 11 months ago
Efficient Discovery of Loop Nests in Execution Traces
Execution and communication traces are central to performance modeling and analysis. Since the traces can be very long, meaningful compression and extraction of representative beha...
Qiang Xu, Jaspal Subhlok, Nathaniel Hammen
DCC
2009
IEEE
14 years 10 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang
DCC
2006
IEEE
14 years 9 months ago
Compressed Data Structures: Dictionaries and Data-Aware Measures
Abstract. We propose measures for compressed data structures, in which space usage is measured in a data-aware manner. In particular, we consider the fundamental dictionary problem...
Ankur Gupta, Wing-Kai Hon, Rahul Shah, Jeffrey Sco...
CISS
2008
IEEE
14 years 4 months ago
Compressed channel sensing
—Reliable wireless communications often requires accurate knowledge of the underlying multipath channel. This typically involves probing of the channel with a known training wave...
Waheed Uz Zaman Bajwa, Jarvis Haupt, Gil M. Raz, R...