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PAMI
2007
196views more  PAMI 2007»
15 years 5 months ago
Clustering and Embedding Using Commute Times
This paper exploits the properties of the commute time between nodes of a graph for the purposes of clustering and embedding, and explores its applications to image segmentation a...
Huaijun Qiu, Edwin R. Hancock
TIP
2010
131views more  TIP 2010»
15 years 16 days ago
Orientation Modulation for Data Hiding in Clustered-Dot Halftone Prints
We present a new framework for data hiding in images printed with clustered dot halftones. Our application scenario, like other hardcopy embedding methods, encounters fundamental c...
Orhan Bulan, Gaurav Sharma, Vishal Monga
ICDM
2006
IEEE
124views Data Mining» more  ICDM 2006»
15 years 12 months ago
Finding "Who Is Talking to Whom" in VoIP Networks via Progressive Stream Clustering
Technologies that use the Internet network to deliver voice communications have the potential to reduce costs and improve access to communications services around the world. Howev...
Olivier Verscheure, Michail Vlachos, Aris Anagnost...
ICML
2010
IEEE
15 years 6 months ago
Local Minima Embedding
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Minyoung Kim, Fernando De la Torre
IGPL
2010
142views more  IGPL 2010»
15 years 3 months ago
Logics of Kripke meta-models
This paper introduces and studies a new type of logical construction, which allows to combine various non-classical propositional logics with the temporal or modal background. The...
Sergey Babenyshev, Vladimir V. Rybakov