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» Evaluating algorithms that learn from data streams
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ALT
2003
Springer
15 years 10 months ago
Can Learning in the Limit Be Done Efficiently?
Abstract. Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to pot...
Thomas Zeugmann
ECML
2007
Springer
16 years 26 days ago
Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search
We discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has been tackled before by upgrading the structure-search algorithm i...
Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendr...
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 7 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
AIEDU
2010
15 years 4 months ago
Supporting Collaborative Learning and E-Discussions Using Artificial Intelligence Techniques
An emerging trend in classrooms is the use of networked visual argumentation tools that allow students to discuss, debate, and argue with one another in a synchronous fashion about...
Bruce M. McLaren, Oliver Scheuer, Jan Miksatko
EDBT
2008
ACM
154views Database» more  EDBT 2008»
16 years 6 months ago
Ring-constrained join: deriving fair middleman locations from pointsets via a geometric constraint
We introduce a novel spatial join operator, the ring-constrained join (RCJ). Given two sets P and Q of spatial points, the result of RCJ consists of pairs p, q (where p P, q Q) ...
Man Lung Yiu, Panagiotis Karras, Nikos Mamoulis