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NPL
2006
85views more  NPL 2006»
14 years 10 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling
97
Voted
ICDM
2010
IEEE
187views Data Mining» more  ICDM 2010»
14 years 8 months ago
Financial Forecasting with Gompertz Multiple Kernel Learning
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...
Han Qin, Dejing Dou, Yue Fang
97
Voted
CISS
2010
IEEE
14 years 1 months ago
Average case analysis of sparse recovery from combined fusion frame measurements
—Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compr...
Petros Boufounos, Gitta Kutyniok, Holger Rauhut
ITS
2004
Springer
155views Multimedia» more  ITS 2004»
15 years 3 months ago
Modeling the Development of Problem Solving Skills in Chemistry with a Web-Based Tutor
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
ICALT
2005
IEEE
15 years 3 months ago
LM-DTM: An Environment for XML-Based, LIP/PAPI-Compliant Deployment, Transformation and Matching of Learner Models
Our shared belief is that learning, like other human activities, cannot and will not be confined within rigidly defined course systems or learning repositories, inclosing learning...
Mohamed Amine Chatti, Ralf Klamma, Christoph Quix,...