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» Learning to rank with multiple objective functions
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103
Voted
ICMCS
2006
IEEE
192views Multimedia» more  ICMCS 2006»
15 years 5 months ago
Classifier Optimization for Multimedia Semantic Concept Detection
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
Sheng Gao, Qibin Sun
TSMC
2008
132views more  TSMC 2008»
14 years 11 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
106
Voted
ICDM
2010
IEEE
226views Data Mining» more  ICDM 2010»
14 years 9 months ago
Edge Weight Regularization over Multiple Graphs for Similarity Learning
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...
81
Voted
IJCNN
2006
IEEE
15 years 5 months ago
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
— We present a simple, intuitive argument based on “invariant imbedding” in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorith...
Eiji Mizutani, Stuart Dreyfus
83
Voted
EVOW
2008
Springer
15 years 1 months ago
Improving Metaheuristic Performance by Evolving a Variable Fitness Function
In this paper we study a complex real world workforce scheduling problem. We apply constructive search and variable neighbourhood search (VNS) metaheuristics and enhance these meth...
Keshav P. Dahal, Stephen Remde, Peter I. Cowling, ...