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PPSN
2004
Springer
14 years 2 months ago
Ensemble Learning with Evolutionary Computation: Application to Feature Ranking
Abstract. Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings ext...
Kees Jong, Elena Marchiori, Michèle Sebag
ICDM
2010
IEEE
197views Data Mining» more  ICDM 2010»
13 years 7 months ago
D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-defined Classification
: D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi HP Labo...
Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yu...
NIPS
2007
13 years 10 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
ICCBR
2007
Springer
14 years 3 months ago
Label Ranking in Case-Based Reasoning
The problem of label ranking has recently been introduced as an extension of conventional classification in the field of machine learning. In this paper, we argue that label ran...
Klaus Brinker, Eyke Hüllermeier
CIKM
2008
Springer
13 years 11 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...