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TSP
2010
14 years 4 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
CORR
2011
Springer
178views Education» more  CORR 2011»
14 years 1 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
FOCM
2011
188views more  FOCM 2011»
14 years 1 months ago
Compressive Wave Computation
This paper considers large-scale simulations of wave propagation phenomena. We argue that it is possible to accurately compute a wavefield by decomposing it onto a largely incomp...
Laurent Demanet, Gabriel Peyré
SIGECOM
2011
ACM
232views ECommerce» more  SIGECOM 2011»
14 years 12 days ago
Near optimal online algorithms and fast approximation algorithms for resource allocation problems
We present algorithms for a class of resource allocation problems both in the online setting with stochastic input and in the offline setting. This class of problems contains man...
Nikhil R. Devanur, Kamal Jain, Balasubramanian Siv...
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
15 years 1 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar