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NIPS
2001
14 years 11 months ago
On the Convergence of Leveraging
We give an unified convergence analysis of ensemble learning methods including e.g. AdaBoost, Logistic Regression and the Least-SquareBoost algorithm for regression. These methods...
Gunnar Rätsch, Sebastian Mika, Manfred K. War...
IJCNN
2006
IEEE
15 years 3 months ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh
NIPS
1990
14 years 10 months ago
Convergence of a Neural Network Classifier
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
John S. Baras, Anthony LaVigna
IJCAI
1989
14 years 10 months ago
Generation, Local Receptive Fields and Global Convergence Improve Perceptual Learning in Connectionist Networks
This paper presents and compares results for three types of connectionist networks on perceptual learning tasks: [A] Multi-layered converging networks of neuron-like units, with e...
Vasant Honavar, Leonard Uhr
AUTOMATICA
2005
116views more  AUTOMATICA 2005»
14 years 9 months ago
Monotonically convergent iterative learning control for linear discrete-time systems
In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking9 error norms are derived. By using the Ma...
Kevin L. Moore, Yangquan Chen, Vikas Bahl