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» Learning Object Context for Adaptive Learning Design
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ESANN
2007
15 years 4 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
129
Voted
NIPS
2000
15 years 3 months ago
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks
It has long been known that lateral inhibition in neural networks can lead to a winner-take-all competition, so that only a single neuron is active at a steady state. Here we show...
Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian...
135
Voted
ATAL
2011
Springer
14 years 2 months ago
Learning action models for multi-agent planning
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
Hankz Hankui Zhuo, Hector Muñoz-Avila, Qian...
153
Voted
PAMI
2012
13 years 5 months ago
Learning Optimal Embedded Cascades
—The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and...
Mohammad Javad Saberian, Nuno Vasconcelos
123
Voted
ICPR
2008
IEEE
16 years 3 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...