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» Bayesian Inference for Sparse Generalized Linear Models
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107
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PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
14 years 11 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
ICASSP
2011
IEEE
14 years 5 months ago
Weighted and structured sparse total least-squares for perturbed compressive sampling
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
Hao Zhu, Georgios B. Giannakis, Geert Leus
147
Voted
CVIU
2007
193views more  CVIU 2007»
15 years 1 months ago
Interpretation of complex scenes using dynamic tree-structure Bayesian networks
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
Sinisa Todorovic, Michael C. Nechyba
177
Voted
3DPVT
2004
IEEE
316views Visualization» more  3DPVT 2004»
15 years 5 months ago
A Statistical Method for Robust 3D Surface Reconstruction from Sparse Data
Abstract-General information about a class of objects, such as human faces or teeth, can help to solve the otherwise ill-posed problem of reconstructing a complete surface from spa...
Volker Blanz, Albert Mehl, Thomas Vetter, Hans-Pet...
CORR
2011
Springer
191views Education» more  CORR 2011»
14 years 8 months ago
A Message-Passing Receiver for BICM-OFDM over Unknown Clustered-Sparse Channels
We propose a factor-graph-based approach to joint channel-estimationand-decoding of bit-interleaved coded orthogonal frequency division multiplexing (BICM-OFDM). In contrast to ex...
Philip Schniter