256 search results - page 7 / 52 » Sparse random graphs with clustering |
NIPS
2008
13 years 9 months ago
2008
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
TKDE
2012
11 years 10 months ago
2012
— This paper presents a method for identifying a set of dense subgraphs of a given sparse graph. Within the main applications of this “dense subgraph problem”, the dense subg...
SIGIR
2009
ACM
14 years 2 months ago
2009
ACM
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web sea...
CVPR
2012
IEEE
11 years 10 months ago
2012
IEEE
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...