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» A Riemannian approach to graph embedding
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ICASSP
2010
IEEE
13 years 9 months ago
Toward signal processing theory for graphs and non-Euclidean data
Graphs are canonical examples of high-dimensional non-Euclidean data sets, and are emerging as a common data structure in many fields. While there are many algorithms to analyze ...
Benjamin A. Miller, Nadya T. Bliss, Patrick J. Wol...
CVPR
2010
IEEE
14 years 5 months ago
Unified Graph Matching in Euclidean Spaces
Graph matching is a classical problem in pattern recognition with many applications, particularly when the graphs are embedded in Euclidean spaces, as is often the case for comput...
Julian McAuley, Teofilo de Campos, Tiberio Caetano
IEEEPACT
2002
IEEE
14 years 1 months ago
A Framework for Parallelizing Load/Stores on Embedded Processors
Many modern embedded processors (esp. DSPs) support partitioned memory banks (also called X-Y memory or dual bank memory) along with parallel load/store instructions to achieve co...
Xiaotong Zhuang, Santosh Pande, John S. Greenland ...
CODES
2001
IEEE
14 years 18 days ago
Hybrid global/local search strategies for dynamic voltage scaling in embedded multiprocessors
In this paper, we explore a hybrid global/local search optimization framework for dynamic voltage scaling in embedded multiprocessor systems. The problem is to find, for a multipr...
Neal K. Bambha, Shuvra S. Bhattacharyya, Jürg...
MM
2004
ACM
167views Multimedia» more  MM 2004»
14 years 2 months ago
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Xiaofei He, Wei-Ying Ma, HongJiang Zhang