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» Conditional expectation and fuzzy regression
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CORR
2007
Springer
112views Education» more  CORR 2007»
13 years 6 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky
AAAI
2011
12 years 6 months ago
Logistic Methods for Resource Selection Functions and Presence-Only Species Distribution Models
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they...
Steven Phillips, Jane Elith
KDD
2007
ACM
138views Data Mining» more  KDD 2007»
14 years 4 days ago
High-quantile modeling for customer wallet estimation and other applications
In this paper we discuss the important practical problem of customer wallet estimation, i.e., estimation of potential spending by customers (rather than their expected spending). ...
Claudia Perlich, Saharon Rosset, Richard D. Lawren...
AI
2000
Springer
13 years 5 months ago
Stochastic dynamic programming with factored representations
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Craig Boutilier, Richard Dearden, Moisés Go...
JAIR
1998
198views more  JAIR 1998»
13 years 5 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...