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JCSS
2008
138views more  JCSS 2008»
14 years 9 months ago
Reducing mechanism design to algorithm design via machine learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
EOR
2007
165views more  EOR 2007»
14 years 9 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
AC
2004
Springer
14 years 9 months ago
The Timeboxing process model for iterative software development
In today's business where speed is of essence, an iterative development approach that allows the functionality to be delivered in parts has become a necessity and an effectiv...
Pankaj Jalote, Aveejeet Palit, Priya Kurien
ISDA
2010
IEEE
14 years 7 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
SIAMREV
2010
108views more  SIAMREV 2010»
14 years 4 months ago
Market Design for Emission Trading Schemes
Abstract. The main thrust of the paper is the design and the numerical analysis of new capand-trade schemes for the control and the reduction of atmospheric pollution. The tools de...
René Carmona, Max Fehr, Juri Hinz, Arnaud P...