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» Applying learning algorithms to preference elicitation
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KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 5 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
IUI
2000
ACM
13 years 9 months ago
Adaptation in automated user-interface design
Design problems involve issues of stylistic preference and flexible standards of success; human designers often proceed by intuition and are unaware of following any strict rule-b...
Jacob Eisenstein, Angel R. Puerta
IJCAI
2007
13 years 6 months ago
Occam's Razor Just Got Sharper
Occam’s razor is the principle that, given two hypotheses consistent with the observed data, the simpler one should be preferred. Many machine learning algorithms follow this pr...
Saher Esmeir, Shaul Markovitch
GECCO
2005
Springer
112views Optimization» more  GECCO 2005»
13 years 11 months ago
Monotonic solution concepts in coevolution
Assume a coevolutionary algorithm capable of storing and utilizing all phenotypes discovered during its operation, for as long as it operates on a problem; that is, assume an algo...
Sevan G. Ficici
ICML
2004
IEEE
13 years 11 months ago
Ensembles of nested dichotomies for multi-class problems
Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression. They can be represented as binary trees ...
Eibe Frank, Stefan Kramer