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IJRR
2011
126views more  IJRR 2011»
13 years 2 months ago
Optimization and learning for rough terrain legged locomotion
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to p...
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, ...
MVA
2000
172views Computer Vision» more  MVA 2000»
13 years 9 months ago
Partial Face Extraction and Recognition Using Radial Basis Function Networks
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
Nan He, Kiminori Sato, Yukitoshi Takahashi
IJACTAICIT
2010
153views more  IJACTAICIT 2010»
13 years 2 months ago
Prediction Using Recurrent Neural Network Based Fuzzy Inference system by the Modified Bees Algorithm
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
Zahra Khanmirzaei, Mohammad Teshnehlab
ICANN
2011
Springer
12 years 11 months ago
Transforming Auto-Encoders
The artificial neural networks that are used to recognize shapes typically use one or more layers of learned feature detectors that produce scalar outputs. By contrast, the comput...
Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang
ICDAR
2007
IEEE
14 years 1 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun