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STOC
2007
ACM
106views Algorithms» more  STOC 2007»
16 years 2 months ago
One sketch for all: fast algorithms for compressed sensing
Compressed Sensing is a new paradigm for acquiring the compressible signals that arise in many applications. These signals can be approximated using an amount of information much ...
Anna C. Gilbert, Martin J. Strauss, Joel A. Tropp,...
ICDAR
2009
IEEE
15 years 8 months ago
Fast Incremental Learning Strategy Driven by Confusion Reject for Online Handwriting Recognition
In this paper, we present a new incremental learning strategy for handwritten character recognition systems. This learning strategy enables the recognition system to learn “rapi...
Abdullah Almaksour, Éric Anquetil
ICPR
2008
IEEE
15 years 8 months ago
Fast multiple instance learning via L1, 2 logistic regression
In this paper, we develop an efficient logistic regression model for multiple instance learning that combines L1 and L2 regularisation techniques. An L1 regularised logistic regr...
Zhouyu Fu, Antonio Robles-Kelly
ECML
2007
Springer
15 years 8 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
PATMOS
2007
Springer
15 years 8 months ago
Fast Calculation of Permissible Slowdown Factors for Hard Real-Time Systems
This work deals with the problem to optimise the energy consumption of an embedded system. On system level, tasks are assumed to have a certain CPU-usage they need for completion. ...
Henrik Lipskoch, Karsten Albers, Frank Slomka