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» Minimax Probability Machine
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94
Voted
ICML
2002
IEEE
16 years 1 months ago
Action Refinement in Reinforcement Learning by Probability Smoothing
In many reinforcement learning applications, the set of possible actions can be partitioned by the programmer into subsets of similar actions. This paper presents a technique for ...
Carles Sierra, Dídac Busquets, Ramon L&oacu...
88
Voted
ECML
2007
Springer
15 years 6 months ago
A Simple Lexicographic Ranker and Probability Estimator
Given a binary classification task, a ranker sorts a set of instances from highest to lowest expectation that the instance is positive. We propose a lexicographic ranker, LexRank,...
Peter A. Flach, Edson Takashi Matsubara
ICML
1999
IEEE
16 years 1 months ago
Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
Rajesh Parekh, Vasant Honavar
85
Voted
COR
2006
64views more  COR 2006»
15 years 21 days ago
Implementing and testing the tabu cycle and conditional probability methods
-- The purpose of this paper is to describe the implementation and testing of the tabu cycle method and two variants of the conditional probability method. These methods were origi...
Manuel Laguna
122
Voted
ACML
2009
Springer
15 years 7 months ago
Conditional Density Estimation with Class Probability Estimators
Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estim...
Eibe Frank, Remco R. Bouckaert