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» On the Network Complexity of Selection
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AAAI
2011
12 years 9 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
IJCV
2010
574views more  IJCV 2010»
13 years 7 months ago
Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding
We propose a novel approach to understanding activities from their partial observations monitored through multiple non-overlapping cameras separated by unknown time gaps. In our...
Chen Change Loy, Tao Xiang, Shaogang Gong
CSCW
2012
ACM
12 years 4 months ago
Social coding in GitHub: transparency and collaboration in an open software repository
Social applications on the web let users track and follow the activities of a large number of others regardless of location or affiliation. There is a potential for this transpare...
Laura A. Dabbish, H. Colleen Stuart, Jason Tsay, J...
STACS
2012
Springer
12 years 4 months ago
Low Randomness Rumor Spreading via Hashing
We consider the classical rumor spreading problem, where a piece of information must be disseminated from a single node to all n nodes of a given network. We devise two simple pus...
George Giakkoupis, Thomas Sauerwald, He Sun, Phili...
INFOCOM
2012
IEEE
11 years 11 months ago
The Variable-Increment Counting Bloom Filter
—Counting Bloom Filters (CBFs) are widely used in networking device algorithms. They implement fast set representations to support membership queries with limited error, and supp...
Ori Rottenstreich, Yossi Kanizo, Isaac Keslassy
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