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ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 8 days ago
Set-Based Boosting for Instance-Level Transfer
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
Eric Eaton, Marie desJardins
ML
2007
ACM
153views Machine Learning» more  ML 2007»
13 years 5 months ago
Multi-Class Learning by Smoothed Boosting
AdaBoost.OC has been shown to be an effective method in boosting “weak” binary classifiers for multi-class learning. It employs the Error-Correcting Output Code (ECOC) method ...
Rong Jin, Jian Zhang 0003
EMNLP
2009
13 years 3 months ago
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Marie...
WWW
2011
ACM
13 years 16 days ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
NIPS
2007
13 years 7 months ago
One-Pass Boosting
This paper studies boosting algorithms that make a single pass over a set of base classifiers. We first analyze a one-pass algorithm in the setting of boosting with diverse base...
Zafer Barutçuoglu, Philip M. Long, Rocco A....