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» Adaptive learning in evolving task allocation networks
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IJCNN
2006
IEEE
14 years 23 days ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
JAIR
2006
102views more  JAIR 2006»
13 years 6 months ago
Multiple-Goal Heuristic Search
This paper presents a new framework for anytime heuristic search where the task is to achieve as many goals as possible within the allocated resources. We show the inadequacy of t...
Dmitry Davidov, Shaul Markovitch
CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 1 months ago
On the Combinatorial Multi-Armed Bandit Problem with Markovian Rewards
We consider a combinatorial generalization of the classical multi-armed bandit problem that is defined as follows. There is a given bipartite graph of M users and N M resources. F...
Yi Gai, Bhaskar Krishnamachari, Mingyan Liu
AAAI
2011
12 years 6 months ago
User-Controllable Learning of Location Privacy Policies With Gaussian Mixture Models
With smart-phones becoming increasingly commonplace, there has been a subsequent surge in applications that continuously track the location of users. However, serious privacy conc...
Justin Cranshaw, Jonathan Mugan, Norman M. Sadeh
ESWA
2006
154views more  ESWA 2006»
13 years 6 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim