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GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
15 years 11 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
SIGGRAPH
2000
ACM
15 years 9 months ago
Style machines
We approach the problem of stylistic motion synthesis by learning motion patterns from a highly varied set of motion capture sequences. Each sequence may have a distinct choreogra...
Matthew Brand, Aaron Hertzmann
EDM
2008
97views Data Mining» more  EDM 2008»
15 years 6 months ago
Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor
Using data from an existing pre-algebra computer-based tutor, we analyzed the covariance of item-types with the goal of describing a more effective way to assign skill labels to it...
Philip I. Pavlik, Hao Cen, Lili Wu, Kenneth R. Koe...
ML
2008
ACM
15 years 5 months ago
A linear fit gets the correct monotonicity directions
Let f be a function on Rd that is monotonic in every variable. There are 2d possible assignments to the directions of monotonicity (two per variable). We provide sufficient condit...
Malik Magdon-Ismail, Joseph Sill
ML
2010
ACM
142views Machine Learning» more  ML 2010»
15 years 3 months ago
Fast adaptive algorithms for abrupt change detection
We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algor...
Daniel Nikovski, Ankur Jain