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191
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JMLR
2010
145views more  JMLR 2010»
15 years 28 days ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
ICCV
2011
IEEE
14 years 6 months ago
Conditional Random Fields for Multi-Camera Object Detection
We formulate a model for multi-class object detection in a multi-camera environment. From our knowledge, this is the first time that this problem is addressed taken into account ...
Xavier Boix, Gemma Roig, Horesh Ben Shitrit, Pasca...
PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
16 years 21 days ago
RTG: A Recursive Realistic Graph Generator Using Random Typing
We propose a new, recursive model to generate realistic graphs, evolving over time. Our model has the following properties: it is (a) flexible, capable of generating the cross pro...
Leman Akoglu, Christos Faloutsos
GI
2003
Springer
15 years 11 months ago
Byzantine Failures and Security: Arbitrary is not (always) Random
: The Byzantine failure model allows arbitrary behavior of a certain fraction of network nodes in a distributed system. It was introduced to model and analyze the effects of very s...
Felix C. Gärtner
159
Voted
INFOCOM
2000
IEEE
15 years 10 months ago
End-to-End Congestion Control Schemes: Utility Functions, Random Losses and ECN Marks
We present a framework for designing end-to-end congestion control schemes in a network where each user may have a different utility function and may experience non-congestion-re...
Srisankar S. Kunniyur, Rayadurgam Srikant