Unsupervised Learning in LSTM Recurrent Neural Networks
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Jürgen Schmidhuber | Nicol N. Schraudolph | Magdalena Klapper-Rybicka | J. Schmidhuber | N. Schraudolph | M. Klapper-Rybicka
[1] Paul A. Viola,et al. Empirical Entropy Manipulation for Real-World Problems , 1995, NIPS.
[2] Zhaoping Li,et al. A Theory of the Visual Motion Coding in the Primary Visual Cortex , 1996, Neural Computation.
[3] Eric Saund,et al. Unsupervised Learning of Mixtures of Multiple Causes in Binary Data , 1993, NIPS.
[4] Peter Dayan,et al. Competition and Multiple Cause Models , 1995, Neural Comput..
[5] Jürgen Schmidhuber,et al. Learning Complex, Extended Sequences Using the Principle of History Compression , 1992, Neural Computation.
[6] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[7] Juergen Schmidhuber,et al. Long Short-Term Memory Learns Context Free and Context Sensitive Languages , 2000 .
[8] David J. Field,et al. What Is the Goal of Sensory Coding? , 1994, Neural Computation.
[9] Jürgen Schmidhuber,et al. Learning Unambiguous Reduced Sequence Descriptions , 1991, NIPS.
[10] Andrzej Cichocki,et al. A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.
[11] PAUL J. WERBOS,et al. Generalization of backpropagation with application to a recurrent gas market model , 1988, Neural Networks.
[12] Ralph Linsker,et al. Self-organization in a perceptual network , 1988, Computer.
[13] H. B. Barlow,et al. Finding Minimum Entropy Codes , 1989, Neural Computation.
[14] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[15] A. Norman Redlich,et al. Redundancy Reduction as a Strategy for Unsupervised Learning , 1993, Neural Computation.
[16] Nicole Norbert Schraudolph. Optimization of entropy with neural networks , 1996 .
[17] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..
[18] Jürgen Schmidhuber,et al. Discovering Predictable Classifications , 1993, Neural Computation.
[19] M. Mozer. Discovering Discrete Distributed Representations with Iterative Competitive Learning , 1990, NIPS 1990.
[20] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[21] Suzanna Becker,et al. Unsupervised Learning Procedures for Neural Networks , 1991, Int. J. Neural Syst..
[22] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[23] Horace Barlow,et al. Understanding Natural Vision , 1983 .
[24] Jürgen Schmidhuber,et al. Recurrent nets that time and count , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.
[25] Jürgen Schmidhuber,et al. Feature Extraction Through LOCOCODE , 1999, Neural Computation.
[26] Peter Tiño,et al. Building predictive models on complex symbolic sequences with a second-order recurrent BCM network with lateral inhibition , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.
[27] Jürgen Schmidhuber. Neural Predictors for Detecting and Removing Redundant Information , 2000 .
[28] S. Hochreiter,et al. Lococode Performs Nonlinear ICA Without Knowing The Number Of Sources , 1999 .
[29] Terrence J. Sejnowski,et al. Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain , 1992, NIPS.
[30] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[31] Jürgen Schmidhuber,et al. Learning Factorial Codes by Predictability Minimization , 1992, Neural Computation.
[32] Günther Palm,et al. On the Information Storage Capacity of Local Learning Rules , 1992, Neural Computation.
[33] Stefanie N. Lindstaedt,et al. Comparison of two Unsupervised Neural Network Models for Redundancy Reduction , 1993 .
[34] R. Zemel. A minimum description length framework for unsupervised learning , 1994 .
[35] N N Schraudolph,et al. Processing images by semi-linear predictability minimization. , 1997, Network.
[36] Geoffrey E. Hinton,et al. Generative models for discovering sparse distributed representations. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[37] Jürgen Schmidhuber,et al. LSTM recurrent networks learn simple context-free and context-sensitive languages , 2001, IEEE Trans. Neural Networks.
[38] Peter Földiák,et al. Sparse coding in the primate cortex , 1998 .
[39] Néstor Parga,et al. Redundancy Reduction and Independent Component Analysis: Conditions on Cumulants and Adaptive Approaches , 1997, Neural Computation.
[40] Geoffrey E. Hinton,et al. Learning Population Codes by Minimizing Description Length , 1993, Neural Computation.
[41] Jürgen Schmidhuber,et al. Learning to Forget: Continual Prediction with LSTM , 2000, Neural Computation.
[42] Sepp Hochreiter,et al. Untersuchungen zu dynamischen neuronalen Netzen , 1991 .
[43] D J Field,et al. Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[44] Jürgen Schmidhuber,et al. Source Separation as a By-Product of Regularization , 1998, NIPS.