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» On the Complexity of Function Learning
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MFCS
2004
Springer
14 years 3 months ago
Approximating Boolean Functions by OBDDs
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
Andre Gronemeier
IJCNN
2000
IEEE
14 years 2 months ago
Storage and Recall of Complex Temporal Sequences through a Contextually Guided Self-Organizing Neural Network
A self-organizing neural network for learning and recall of complex temporal sequences is proposed. we consider a single sequence with repeated items, or several sequences with a c...
Guilherme De A. Barreto, Aluizio F. R. Araú...
IJCNN
2000
IEEE
14 years 1 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Sander M. Bohte, Johannes A. La Poutré, Joo...
ESANN
2006
13 years 11 months ago
Synthesis of maximum margin and multiview learning using unlabeled data
In this presentation we show the semi-supervised learning with two input sources can be transformed into a maximum margin problem to be similar to a binary SVM. Our formulation exp...
Sándor Szedmák, John Shawe-Taylor
ICML
2009
IEEE
14 years 10 months ago
Importance weighted active learning
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Alina Beygelzimer, Sanjoy Dasgupta, John Langford