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» Discovering Classification from Data of Multiple Sources
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ICCV
2011
IEEE
14 years 1 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa
103
Voted
SUTC
2008
IEEE
15 years 8 months ago
Effective Feature Space Reduction with Imbalanced Data for Semantic Concept Detection
Semantic understanding of multimedia content has become a very popular research topic in recent years. Semantic concept detection algorithms face many challenges such as the seman...
Lin Lin, Guy Ravitz, Mei-Ling Shyu, Shu-Ching Chen
144
Voted
CODES
2010
IEEE
14 years 11 months ago
Automatic memory partitioning: increasing memory parallelism via data structure partitioning
In high-level synthesis, pipelined designs are often restricted by the number of memory banks available to the synthesis system. Using multiple memory banks can improve the perfor...
Yosi Ben-Asher, Nadav Rotem
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
15 years 6 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how di...
Xiao Zhang, Prasenjit Mitra
IJCAI
2003
15 years 3 months ago
Integrating Background Knowledge Into Text Classification
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Sarah Zelikovitz, Haym Hirsh