EVALUATING LONG-TERM DEPENDENCYBENCHMARK PROBLEMS BY RANDOM GUESSINGJ
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[1] Taylor L. Booth,et al. Grammatical Inference: Introduction and Survey-Part I , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Stephen I. Gallant,et al. A connectionist learning algorithm with provable generalization and scaling bounds , 1990, Neural Networks.
[3] Sepp Hochreiter,et al. Untersuchungen zu dynamischen neuronalen Netzen , 1991 .
[4] Michael C. Mozer,et al. Induction of Multiscale Temporal Structure , 1991, NIPS.
[5] Jürgen Schmidhuber,et al. Learning Complex, Extended Sequences Using the Principle of History Compression , 1992, Neural Computation.
[6] Kevin J. Lang. Random DFA's can be approximately learned from sparse uniform examples , 1992, COLT '92.
[7] Raymond L. Watrous,et al. Induction of Finite-State Languages Using Second-Order Recurrent Networks , 1992, Neural Computation.
[8] Yoshua Bengio,et al. Credit Assignment through Time: Alternatives to Backpropagation , 1993, NIPS.
[9] C. Lee Giles,et al. Experimental Comparison of the Effect of Order in Recurrent Neural Networks , 1993, Int. J. Pattern Recognit. Artif. Intell..
[10] Yoshua Bengio,et al. An Input Output HMM Architecture , 1994, NIPS.
[11] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[12] Panagiotis Manolios,et al. First-Order Recurrent Neural Networks and Deterministic Finite State Automata , 1994, Neural Computation.
[13] Peter Tiňo,et al. Learning long-term dependencies is not as difficult with NARX recurrent neural networks , 1995 .
[14] Barak A. Pearlmutter. Gradient calculations for dynamic recurrent neural networks: a survey , 1995, IEEE Trans. Neural Networks.
[15] Peter Tiño,et al. Learning long-term dependencies is not as difficult with NARX networks , 1995, NIPS.
[16] Yoshua Bengio,et al. Hierarchical Recurrent Neural Networks for Long-Term Dependencies , 1995, NIPS.
[17] Michael I. Jordan,et al. Exploiting Tractable Substructures in Intractable Networks , 1995, NIPS.
[18] Michael I. Jordan,et al. Hidden Markov Decision Trees , 1996, NIPS.
[19] Jürgen Schmidhuber,et al. LSTM can Solve Hard Long Time Lag Problems , 1996, NIPS.
[20] Jürgen Schmidhuber,et al. Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability , 1997, Neural Networks.
[21] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[22] Jürgen Schmidhuber,et al. Flat Minima , 1997, Neural Computation.