WATCHING THE TRANSIENTS : VIEWING A SIMPLE RECURRENT NETWORK AS A LIMITED COUNTER
暂无分享,去创建一个
[1] J. Elman. Distributed Representations, Simple Recurrent Networks, And Grammatical Structure , 1991 .
[2] Stuart M. Shieber,et al. Foundational issues in natural language processing , 1991 .
[3] Cristopher Moore,et al. Dynamical Recognizers: Real-Time Language Recognition by Analog Computers , 1998, Theor. Comput. Sci..
[4] John F. Kolen,et al. Exploring the computational capabilities of recurrent neural networks , 1995 .
[5] Janet Wiles,et al. Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting , 1997, NIPS.
[6] Mark F. St. John,et al. The Story Gestalt: A Model of Knowledge-Intensive Processes in Text Comprehension , 1992, Cogn. Sci..
[7] Kurt Hornik,et al. A Convergence Result for Learning in Recurrent Neural Networks , 1994, Neural Computation.
[8] Mike Casey,et al. The Dynamics of Discrete-Time Computation, with Application to Recurrent Neural Networks and Finite State Machine Extraction , 1996, Neural Computation.
[9] Hava T. Siegelmann,et al. On the Computational Power of Neural Nets , 1995, J. Comput. Syst. Sci..
[10] Marshall C. Yovits,et al. Ohio State University , 1974, SGAR.
[11] Ronald J. Williams,et al. Experimental Analysis of the Real-time Recurrent Learning Algorithm , 1989 .
[12] S. Smale,et al. On a theory of computation and complexity over the real numbers; np-completeness , 1989 .
[13] Pekka Orponen,et al. On the Effect of Analog Noise in Discrete-Time Analog Computations , 1996, Neural Computation.
[14] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[15] Andrew S. Noetzel,et al. Sequence Recognition with Recurrent Neural Networks , 1993 .
[16] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[17] James L. McClelland,et al. Graded state machines: the representation of temporal contingencies in feedback networks , 1995 .
[18] Jeffrey L. Elman,et al. A PDP Approach to Processing Center-Embedded Sentences , 1992 .
[19] Jordan B. Pollack,et al. Recursive Distributed Representations , 1990, Artif. Intell..
[20] Walter S. Stolz,et al. A study of the ability to decode grammatically novel sentences , 1967 .
[21] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[22] Peter Tiňo,et al. Finite State Machines and Recurrent Neural Networks -- Automata and Dynamical Systems Approaches , 1995 .
[23] Jordan B. Pollack,et al. Analysis of Dynamical Recognizers , 1997, Neural Computation.
[24] Arnold L. Rosenberg,et al. Real-Time Definable Languages , 1967, JACM.
[25] James L. McClelland,et al. Finite State Automata and Simple Recurrent Networks , 1989, Neural Computation.
[26] Jeffrey D. Ullman,et al. Introduction to Automata Theory, Languages and Computation , 1979 .
[27] C. Lee Giles,et al. Extracting and Learning an Unknown Grammar with Recurrent Neural Networks , 1991, NIPS.
[28] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[29] Johnson Murdoch Hart. Formal properties of local-adjunct languages (lal's). , 1972 .
[30] Nick Chater,et al. Toward a connectionist model of recursion in human linguistic performance , 1999 .