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» Conditional Models for Non-smooth Ranking Loss Functions
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RT
2005
Springer
14 years 1 months ago
Perceptually Based Tone Mapping of High Dynamic Range Image Streams
This paper presents a new perceptually based tone mapping operator that represents scene visibility under timevarying, high dynamic range conditions. The operator is based on a ne...
Piti Irawan, James A. Ferwerda, Stephen R. Marschn...
JMLR
2010
143views more  JMLR 2010»
13 years 6 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
EMNLP
2008
13 years 9 months ago
Mining and Modeling Relations between Formal and Informal Chinese Phrases from Web Corpora
We present a novel method for discovering and modeling the relationship between informal Chinese expressions (including colloquialisms and instant-messaging slang) and their forma...
Zhifei Li, David Yarowsky
CSDA
2008
94views more  CSDA 2008»
13 years 7 months ago
Robust model selection using fast and robust bootstrap
Robust model selection procedures control the undue influence that outliers can have on the selection criteria by using both robust point estimators and a bounded loss function wh...
Matias Salibian-Barrera, Stefan Van Aelst
SIGIR
2011
ACM
12 years 10 months ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen