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» A Portfolio Approach to Algorithm Selection
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JCP
2007
143views more  JCP 2007»
13 years 7 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
JCSS
2007
68views more  JCSS 2007»
13 years 7 months ago
Portfolio and investment risk analysis on global grids
The financial services industry today produces and consumes huge amounts of data and the processes involved in analysing these data are equally huge especially in terms of their c...
Rafael Moreno-Vozmediano, Krishna Nadiminti, Sriku...
IFSA
2007
Springer
110views Fuzzy Logic» more  IFSA 2007»
14 years 1 months ago
Selection Criteria for Fuzzy Unsupervised Learning: Applied to Market Segmentation
The use of unsupervised fuzzy learning methods produces a large number of alternative classifications. This paper presents and analyzes a series of criteria to select the most sui...
Germán Sánchez, Núria Agell, ...
ANOR
2007
165views more  ANOR 2007»
13 years 7 months ago
Financial scenario generation for stochastic multi-stage decision processes as facility location problems
The quality of multi-stage stochastic optimization models as they appear in asset liability management, energy planning, transportation, supply chain management, and other applicat...
Ronald Hochreiter, Georg Ch. Pflug
AAAI
2012
11 years 9 months ago
Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...