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» On learning with dissimilarity functions
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WSC
2004
14 years 11 months ago
Function-Approximation-Based Importance Sampling for Pricing American Options
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
Nomesh Bolia, Sandeep Juneja, Paul Glasserman
JODL
2006
116views more  JODL 2006»
14 years 10 months ago
Appearance and functionality of electronic books
We present the results and the lessons learned from two separate and independent studies into the design, development, and evaluation of electronic books for information access: th...
Fabio Crestani, Monica Landoni, Massimo Melucci
JSW
2007
133views more  JSW 2007»
14 years 10 months ago
New Functions for Unsupervised Asymmetrical Paraphrase Detection
Abstract— Monolingual text-to-text generation is an emerging research area in Natural Language Processing. One reason for the interest in such generation systems is the possibili...
João Cordeiro, Gaël Dias, Pavel Brazdi...
AI
1999
Springer
14 years 9 months ago
Topological Inference of Teleology: Deriving Function from Structure via Evidential Reasoning
Reasoning about the physical world is a central human cognitive activity. One aspect of such reasoning is the inference of function from the structure of the artifacts one encount...
John O. Everett
JMLR
2011
145views more  JMLR 2011»
14 years 5 months ago
Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Func
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
Jim C. Huang, Brendan J. Frey