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Slow Feature Analysis (SFA) extracts features representing the underlying causes of changes within a temporally coherent high-dimensional raw sensory input signal.
Probability, random variables, and stochastic processes
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A unified neural bigradient algorithm for robust pca and mca
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A unified algorithm for principal and minor components extraction
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Learning the parts of objects by non-negative matrix factorization
Lee, D. and Seung, H. (1999) · 1999
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Spatial view cells and the representation of place in the primate hippocampus
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Estimating driving forces of nonstationary time series with slow feature analysis
Wiskott, L. (2003) · 2003
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A spatio-temporal extension to isomap nonlinear dimension reduction
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Microstructure of a spatial map in the entorhinal cortex
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A new algorithm for sequential minor component analysis
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Optimal in-place learning and the lobe component analysis
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Slowness and sparseness lead to place, head-direction, and spatial-view cells
Franzius, M., Sprekeler, H., and Wiskott, L. (2007) · 2007
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Neural predictors for detecting and removing redundant information
Schmidhuber, J. (1999) · 1999
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Algorithms for accelerated convergence of adaptive pca
Chatterjee, C., Kang, Z., and Roychowdhury, V. (2000) · 2000
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Redundancy reduction revisited
Barlow, H. (2001) · 2001
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Sequential extraction of minor components
Chen, T., Amari, S., and Murata, N. (2001) · 2001
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Theoretical neuroscience: Computational and mathematical modeling of neural systems
Dayan, P. and Abbott, L. (2001) · 2001
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Unsupervised learning in LSTM recurrent neural networks
Klapper-Rybicka, M., Schraudolph, N. N., and Schmidhuber, J. (2001) · 2001
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Convergence analysis of a simple minor component analysis algorithm
Peng, D., Yi, Z., and Luo, W. (2007) · 2007
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Modular toolkit for data processing (mdp): a python data processing framework
T. Zito, N. Wilbert, L. W. and Berkes, P. (2008) · 2008
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An open-source simulator for cognitive robotics research: The prototype of the icub humanoid robot simulator
V. Tikhanoff, A. Cangelosi, P. F. G. M. L. N. and Nori, F. (2008) · 2008
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Slow, decorrelated features for pretraining complex cell-like networks
Bergstra, J. and Bengio, Y. (2009) · 2009
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Unsupervised feature learning for audio classification using convolutional deep belief networks
Lee, H., Largman, Y., Pham, P., and Ng, A. (2010) · 2010
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Reinforcement learning on slow features of high-dimensional input streams
Legenstein, R., Wilbert, N., and Wiskott, L. (2010) · 2010
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Formal theory of creativity, fun, and intrinsic motivation (1990–2010)
Schmidhuber, J. (2010) · 2010
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An extension of slow feature analysis for nonlinear blind source separation
Sprekeler, H., Zito, T., and Wiskott, L. (2010) · 2010
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Sequential constant size compressors for reinforcement learning
Gisslen, L., Luciw, M., Graziano, V., and Schmidhuber, J. (2011) · 2011
Closest in time.
Slow feature analysis
Wiskott, L., Berkes, P., Franzius, M., Sprekeler, H., and Wilbert, N. (2011) · 2011
Closest in time.