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» Convergence Properties of the K-Means Algorithms
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FUZZIEEE
2007
IEEE
15 years 6 months ago
Fuzzy Approximation for Convergent Model-Based Reinforcement Learning
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
KBSE
2005
IEEE
15 years 5 months ago
Learning to verify branching time properties
We present a new model checking algorithm for verifying computation tree logic (CTL) properties. Our technique is based on using language inference to learn the fixpoints necessar...
Abhay Vardhan, Mahesh Viswanathan
INFOCOM
2002
IEEE
15 years 4 months ago
Improving BGP Convergence Through Consistency Assertions
— This paper presents a new mechanism for improving the convergence properties of path vector routing algorithms, such as BGP. Using a route’s path information, we develop two ...
Dan Pei, Xiaoliang Zhao, Lan Wang, Daniel Massey, ...
NIPS
2008
15 years 1 months ago
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g.,...
Dotan Di Castro, Dmitry Volkinshtein, Ron Meir
EDBT
2004
ACM
142views Database» more  EDBT 2004»
15 years 11 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...