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» Learning, Forgetting, and Sales
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ICML
2010
IEEE
13 years 6 months ago
Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
Nicholas Bartlett, David Pfau, Frank Wood
ICANN
2003
Springer
13 years 10 months ago
Meta-learning for Fast Incremental Learning
Model based learning systems usually face to a problem of forgetting as a result of the incremental learning of new instances. Normally, the systems have to re-learn past instances...
Takayuki Oohira, Koichiro Yamauchi, Takashi Omori
IJCNN
2006
IEEE
13 years 11 months 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...
ATAL
2011
Springer
12 years 5 months ago
Forgetting through generalisation: a companion with selective memory
This research investigates event generalisation in computational episodic memory for artificial companions. Two studies indicated a preference of a biologically-inspired selectiv...
Mei Yii Lim, Ruth Aylett, Patrícia Amâ...
GECCO
2007
Springer
147views Optimization» more  GECCO 2007»
13 years 11 months ago
GAINS: genetic algorithms for increasing net sales of a mobile reverse demand communication system
In this paper, I describe MRDCOM, a mobile reverse-demand communication system for the pizza industry. The web-based system will support student (buyer) sign-up and will be capabl...
Michael Henry Wolk