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116
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ICDE
2010
IEEE
222views Database» more  ICDE 2010»
14 years 11 months ago
Finding Clusters in subspaces of very large, multi-dimensional datasets
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
123
Voted
TSP
2010
14 years 7 months ago
Randomized and distributed self-configuration of wireless networks: two-layer Markov random fields and near-optimality
Abstract--This work studies the near-optimality versus the complexity of distributed configuration management for wireless networks. We first develop a global probabilistic graphic...
Sung-eok Jeon, Chuanyi Ji
CORR
2011
Springer
178views Education» more  CORR 2011»
14 years 4 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
PERVASIVE
2011
Springer
14 years 3 months ago
Recognizing Whether Sensors Are on the Same Body
As personal health sensors become ubiquitous, we also expect them to become interoperable. That is, instead of closed, end-to-end personal health sensing systems, we envision stand...
Cory Cornelius, David Kotz
252
Voted

Book
5396views
16 years 11 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li