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GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
14 years 1 months ago
Factorial representations to generate arbitrary search distributions
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
Marc Toussaint
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
13 years 12 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman
IWC
2008
99views more  IWC 2008»
13 years 7 months ago
Pedagogy and usability in interactive algorithm visualizations: Designing and evaluating CIspace
Interactive algorithm visualizations (AVs) are powerful tools for teaching and learning concepts that are difficult to describe with static media alone. However, while countless A...
Saleema Amershi, Giuseppe Carenini, Cristina Conat...
EPIA
2009
Springer
14 years 2 months ago
An ILP System for Learning Head Output Connected Predicates
Inductive Logic Programming (ILP) [1] systems are general purpose learners that have had significant success on solving a number of relational problems, particularly from the biol...
José Carlos Almeida Santos, Alireza Tamaddo...
WWW
2007
ACM
14 years 8 months ago
Hierarchical, perceptron-like learning for ontology-based information extraction
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Yaoyong Li, Kalina Bontcheva