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TSP
2010
13 years 2 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
KDD
2004
ACM
181views Data Mining» more  KDD 2004»
14 years 7 months ago
Column-generation boosting methods for mixture of kernels
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
Jinbo Bi, Tong Zhang, Kristin P. Bennett
ICML
2004
IEEE
14 years 8 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ICC
2008
IEEE
115views Communications» more  ICC 2008»
14 years 1 months ago
Joint Power Scheduling and Estimator Design for Sensor Networks Across Parallel Channels
—This paper addresses the joint estimator and power optimization problem for a sensor network whose mission is to estimate an unknown parameter. We assume a two-hop network where...
Lauren M. Huie, Xiang He, Aylin Yener
CODES
2007
IEEE
14 years 1 months ago
Locality optimization in wireless applications
There is a strong need now for compilers of embedded systems to find effective ways of optimizing series of loop-nests, wherein majority of the memory references occur in the fo...
Javed Absar, Min Li, Praveen Raghavan, Andy Lambre...