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ICDM
2008
IEEE
110views Data Mining» more  ICDM 2008»
14 years 1 months ago
Start Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
David A. Cieslak, Nitesh V. Chawla
IROS
2006
IEEE
113views Robotics» more  IROS 2006»
14 years 1 months ago
Policy Gradient Methods for Robotics
— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
Jan Peters, Stefan Schaal
CIDM
2009
IEEE
14 years 2 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
ICPR
2010
IEEE
13 years 6 months ago
Learning Non-Linear Dynamical Systems by Alignment of Local Linear Models
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
Masao Joko, Yoshinobu Kawahara, Takehisa Yairi
NIPS
2008
13 years 8 months ago
Simple Local Models for Complex Dynamical Systems
We present a novel mathematical formalism for the idea of a "local model" of an uncontrolled dynamical system, a model that makes only certain predictions in only certai...
Erik Talvitie, Satinder Singh