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ICANN
2007
Springer
16 years 15 days ago
Incremental and Decremental Learning for Linear Support Vector Machines
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Enrique Romero, Ignacio Barrio, Lluís Belan...
DM
2006
91views more  DM 2006»
15 years 6 months ago
Fast perfect sampling from linear extensions
In this paper, we study the problem of sampling (exactly) uniformly from the set of linear extensions of an arbitrary partial order. Previous Markov chain techniques have yielded ...
Mark Huber
JCC
2002
73views more  JCC 2002»
15 years 6 months ago
Linear scaling approaches to quantum macromolecular similarity: Evaluating the similarity function
: The evaluation of the electron density based similarity function scales quadratically with respect to the size of the molecules for simplified, atomic shell densities. Due to the...
Pere Constans
SIGPRO
2002
80views more  SIGPRO 2002»
15 years 6 months ago
Design of optimum high-order finite-wordlength digital FIR filters with linear phase
Abstract-A novel iterative quantization procedure for the design of finite wordlength linear phase FIR filters of high order and minimum frequency domain error is proposed: a one b...
Gennaro Evangelista
CORR
2011
Springer
148views Education» more  CORR 2011»
15 years 1 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Emmanuel J. Candès, Mark A. Davenport