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» Learning Monotonic Linear Functions
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ASC
2007
13 years 9 months ago
An approximate stability analysis of nonlinear systems described by Universal Learning Networks
Stability is one of the most important subjects in control systems. As for the stability of nonlinear dynamical systems, Lyapunov’s direct method and linearized stability analys...
Kotaro Hirasawa, Shingo Mabu, Shinji Eto, Jinglu H...
PRICAI
2000
Springer
14 years 1 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
JMLR
2006
134views more  JMLR 2006»
13 years 9 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz
CORR
2008
Springer
127views Education» more  CORR 2008»
13 years 9 months ago
MAPEL: Achieving Global Optimality for a Non-convex Wireless Power Control Problem
Achieving weighted throughput maximization (WTM) through power control has been a long standing open problem in interference-limited wireless networks. The complicated coupling bet...
Liping Qian, Ying Jun Zhang, Jianwei Huang
ECML
2003
Springer
14 years 2 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank