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» The complexity of learning SUBSEQ(A)
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KDD
1998
ACM
120views Data Mining» more  KDD 1998»
15 years 10 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen
173
Voted
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
15 years 10 months ago
Evolution of Goal-Directed Behavior from Limited Information in a Complex Environment
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...
Matthew R. Glickman, Katia P. Sycara
SIGDIAL
2010
15 years 4 months ago
Dialogue Act Modeling in a Complex Task-Oriented Domain
Classifying the dialogue act of a user utterance is a key functionality of a dialogue management system. This paper presents a data-driven dialogue act classifier that is learned ...
Kristy Elizabeth Boyer, Eun Y. Ha, Robert Phillips...
182
Voted
ICCV
2007
IEEE
16 years 8 months ago
Unsupervised Joint Alignment of Complex Images
Many recognition algorithms depend on careful positioning of an object into a canonical pose, so the position of features relative to a fixed coordinate system can be examined. Cu...
Gary B. Huang, Vidit Jain, Erik G. Learned-Miller
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 9 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski