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NIPS
2008
15 years 4 months ago
Sparse Signal Recovery Using Markov Random Fields
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...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
MMM
2009
Springer
218views Multimedia» more  MMM 2009»
16 years 11 days ago
Sparse Multiscale Patches (SMP) for Image Categorization
Abstract. In this paper we address the task of image categorization using a new similarity measure on the space of Sparse Multiscale Patches (SMP). SMPs are based on a multiscale t...
Paolo Piro, Sandrine Anthoine, Eric Debreuve, Mich...
139
Voted
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 8 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
ICASSP
2010
IEEE
15 years 2 months ago
Exploring statistical properties for semantic annotation: sparse distributed and convergent assumptions for keywords
Does there exist a compact set of visual topics in form of keyword clusters capable to represent all images visual content within an acceptable error? In this paper, we answer thi...
Xianming Liu, Hongxun Yao, Rongrong Ji
131
Voted
MM
2005
ACM
122views Multimedia» more  MM 2005»
15 years 9 months ago
Image clustering with tensor representation
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
Xiaofei He, Deng Cai, Haifeng Liu, Jiawei Han