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KDD
2012
ACM
220views Data Mining» more  KDD 2012»
8 years 2 months ago
ComSoc: adaptive transfer of user behaviors over composite social network
Accurate prediction of user behaviors is important for many social media applications, including social marketing, personalization and recommendation, etc. A major challenge lies ...
ErHeng Zhong, Wei Fan, Junwei Wang, Lei Xiao, Yong...
JMLR
2012
8 years 2 months ago
SpeedBoost: Anytime Prediction with Uniform Near-Optimality
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Alexander Grubb, Drew Bagnell
JMLR
2010
125views more  JMLR 2010»
9 years 6 months ago
On utility of gene set signatures in gene expression-based cancer class prediction
Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
9 years 9 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...
CORR
2002
Springer
79views Education» more  CORR 2002»
9 years 11 months ago
Technical Note: Bias and the Quantification of Stability
Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should al...
Peter D. Turney
ARTMED
2004
133views more  ARTMED 2004»
9 years 11 months ago
Bayesian network multi-classifiers for protein secondary structure prediction
Successful secondary structure predictions provide a starting point for direct tertiary structure modelling, and also can significantly improve sequence analysis and sequence-stru...
Víctor Robles, Pedro Larrañaga, Jos&...
ESWA
2007
146views more  ESWA 2007»
9 years 11 months ago
A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy
Two parameters, C and r, must be carefully predetermined in establishing an efficient support vector machine (SVM) model. Therefore, the purpose of this study is to develop a gene...
Chih-Hung Wu, Gwo-Hshiung Tzeng, Yeong-Jia Goo, We...
ICMLA
2008
10 years 1 months ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier
ICMLA
2008
10 years 1 months ago
New Insights into Learning Algorithms and Datasets
We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
Jun Won Lee, Christophe G. Giraud-Carrier
EDM
2010
113views Data Mining» more  EDM 2010»
10 years 1 months ago
Using multiple Dirichlet distributions to improve parameter plausibility
Predictive accuracy and parameter plausibility are two major desired aspects for a student modeling approach. Knowledge tracing, the most commonly used approach, suffers from local...
Yue Gong, Joseph E. Beck, Neil T. Heffernan
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