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» Learning Functions from Imperfect Positive Data
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134
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ICDM
2006
IEEE
226views Data Mining» more  ICDM 2006»
15 years 8 months ago
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Jing Gao, Pang-Ning Tan
119
Voted
ECAI
2004
Springer
15 years 8 months ago
Applying Affective Tactics for a Better Learning
This paper describes the Mediating Agent, an animated pedagogical agent inserted in a computational system for distance learning, which has the goal of motivating the student to le...
Patrícia Augustin Jaques, Rosa Maria Vicari...
122
Voted
ICGI
2010
Springer
15 years 3 months ago
Distributional Learning of Some Context-Free Languages with a Minimally Adequate Teacher
Angluin showed that the class of regular languages could be learned from a Minimally Adequate Teacher (mat) providing membership and equivalence queries. Clark and Eyraud (2007) sh...
Alexander Clark
132
Voted
CORR
2011
Springer
192views Education» more  CORR 2011»
14 years 9 months ago
Distribution-Independent Evolvability of Linear Threshold Functions
Valiant’s (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold ...
Vitaly Feldman
104
Voted
NIPS
1998
15 years 4 months ago
Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations
A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, ho...
Michael S. Lewicki, Terrence J. Sejnowski