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» Learning to Rank with Supplementary Data
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IR
2010
13 years 6 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 1 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
MM
2009
ACM
221views Multimedia» more  MM 2009»
14 years 2 months ago
Using large-scale web data to facilitate textual query based retrieval of consumer photos
The rapid popularization of digital cameras and mobile phone cameras has lead to an explosive growth of consumer photo collections. In this paper, we present a (quasi) real-time t...
Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo
ICMLA
2007
13 years 9 months ago
Memory-based context-sensitive spelling correction at web scale
We study the problem of correcting spelling mistakes in text using memory-based learning techniques and a very large database of token n-gram occurrences in web text as training d...
Andrew Carlson, Ian Fette
IJCV
2011
264views more  IJCV 2011»
13 years 2 months ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman