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KDD
2006
ACM
130views Data Mining» more  KDD 2006»
16 years 4 months ago
Discovering significant rules
In many applications, association rules will only be interesting if they represent non-trivial correlations between all constituent items. Numerous techniques have been developed ...
Geoffrey I. Webb
CDC
2009
IEEE
107views Control Systems» more  CDC 2009»
15 years 9 months ago
Learning approaches to the Witsenhausen counterexample from a view of potential games
— Since Witsenhausen put forward his remarkable counterexample in 1968, there have been many attempts to develop efficient methods for solving this non-convex functional optimiz...
Na Li, Jason R. Marden, Jeff S. Shamma
NIPS
1998
15 years 5 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
INFOCOM
2009
IEEE
15 years 11 months ago
Fast Algorithms and Performance Bounds for Sum Rate Maximization in Wireless Networks
Abstract— Sum rate maximization by power control is an important, challenging, and extensively studied problem in wireless networks. It is a nonconvex optimization problem and ac...
Chee-Wei Tan, Mung Chiang, R. Srikant
PPSN
2004
Springer
15 years 9 months ago
Multi-objective Optimisation by Co-operative Co-evolution
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA) and four evolutionary multiobjective optimisation algorithms (EMOAs): a multi-ob...
Kuntinee Maneeratana, Kittipong Boonlong, Nachol C...