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ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
14 years 1 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
IJON
2000
85views more  IJON 2000»
13 years 7 months ago
Hebbian learning and temporary storage in the convergence-zone model of episodic memory
The Convergence-Zone model shows how sparse, random memory patterns can lead to one-shot storage and high capacity in the hippocampal component of the episodic memory system. This...
Michael Howe, Risto Miikkulainen
CCECE
2006
IEEE
14 years 1 months ago
A Dynamic Associative E-Learning Model based on a Spreading Activation Network
Presenting information to an e-learning environment is a challenge, mostly, because ofthe hypertextlhypermedia nature and the richness ofthe context and information provides. This...
Phongchai Nilas, Nilamit Nilas, Somsak Mitatha
SIGMETRICS
1998
ACM
13 years 11 months ago
Modeling Set Associative Caches Behavior for Irregular Computations
While much work has been devoted to the study of cache behavior during the execution of codes with regular access patterns, little attention has been paid to irregular codes. An i...
Basilio B. Fraguela, Ramon Doallo, Emilio L. Zapat...
CONNECTION
2004
98views more  CONNECTION 2004»
13 years 7 months ago
Self-refreshing memory in artificial neural networks: learning temporal sequences without catastrophic forgetting
While humans forget gradually, highly distributed connectionist networks forget catastrophically: newly learned information often completely erases previously learned information. ...
Bernard Ans, Stephane Rousset, Robert M. French, S...