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» Dimensionality reduction and generalization
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ICASSP
2011
IEEE
14 years 10 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...
CORR
2012
Springer
225views Education» more  CORR 2012»
14 years 2 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma
DAC
2002
ACM
16 years 7 months ago
DRG-cache: a data retention gated-ground cache for low power
In this paper we propose a novel integrated circuit and architectural level technique to reduce leakage power consumption in high performance cache memories using single Vt (trans...
Amit Agarwal, Hai Li, Kaushik Roy
IWCMC
2009
ACM
16 years 1 months ago
Effect of feedback prediction on OFDMA system throughput
In wireless communication systems, adaptive modulation and coding (AMC) is used to improve the downlink (DL) spectral efficiency by exploiting the underlying channel condition. Ho...
Mohammad Abdul Awal, Lila Boukhatem
JACM
2006
99views more  JACM 2006»
15 years 6 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller