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» Symbolic methodology for numeric data mining
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DMIN
2009
142views Data Mining» more  DMIN 2009»
13 years 2 months ago
Action Selection in Customer Value Optimization: An Approach Based on Covariate-Dependent Markov Decision Processes
Typical methods in CRM marketing include action selection on the basis of Markov Decision Processes with fixed transition probabilities on the one hand, and scoring customers separ...
Angi Roesch, Harald Schmidbauer
DSN
2002
IEEE
13 years 9 months ago
Pinpoint: Problem Determination in Large, Dynamic Internet Services
Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today’s large, distributed, and dynamic application e...
Mike Y. Chen, Emre Kiciman, Eugene Fratkin, Armand...
ISSAC
2007
Springer
130views Mathematics» more  ISSAC 2007»
13 years 11 months ago
On probabilistic analysis of randomization in hybrid symbolic-numeric algorithms
Algebraic randomization techniques can be applied to hybrid symbolic-numeric algorithms. Here we consider the problem of interpolating a sparse rational function from noisy values...
Erich Kaltofen, Zhengfeng Yang, Lihong Zhi
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 5 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
PAISI
2010
Springer
13 years 2 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...