Markovian bias of neural-based architectures with

Markovian bias of neural-based architectures with

Cached

Download Links

by Peter Tiňo , Barbara Hammer , Mikael Bodén

Citations:

BibTeX

@MISC{Tiňo_markovianbias,
    author = {Peter Tiňo and Barbara Hammer and Mikael Bodén},
    title = {Markovian bias of neural-based architectures with},
    year = {}
}

Bookmark

OpenURL

Abstract

feedback connections

Citations

2726	The self-organizing map - Kohonen - 1990
976	Multilayer feedforward networks are universal approximators - Hornik, Stinchcombe, et al. - 1989
544	Fractals Everywhere - Barnsley - 1988
429	Fractal Geometry - Mathematical Foundations and Applications - Falconer - 1990
368	A Learning Algorithm for Continually Running Fully Recurrent Neural Networks’, Neural computation - Williams, Zipser - 1989
327	Fitting a Mixture Model by Expectation Maximization to Discover Motifs in Biopolymers - Bailey, Elkan - 1994
252	Bioinformatics: The Machine Learning Approach, 2nd edn. (Adaptive Computation and Machine - Baldi, Brunak - 2001
221	Structural risk minimization over data-dependent hierarchies - Shawe-Taylor, Bartlett, et al. - 1940
217	K.: Neural-gas network for vector quantization and its application to time-series prediction - Martinetz, Schulten - 1993
207	DNA binding sites: representation and discovery - Stormo - 2000
193	Real-time computing without stable states: A new framework for neural computation based on perturbations - Maass, Natschlager, et al. - 2002
133	A universal data compression system - Rissanen - 1983
91	The "echo state" approach to analysing and training recurrent neural networks-with an erratum note - Jaeger - 2001
91	Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication - Jaeger, Haas - 2004
91	Pollastri G: Exploiting the past and the future in protein secondary structure prediction. Bioinformatics - Baldi, Brunak, et al. - 1999
90	Toward a connectionist model of recursion in human linguistic performance - Christiansen, Chater - 1999
84	Improved prediction of signal peptides: SignalP 3.0 - Bendtsen, Nielsen, et al. - 2004
70	Analog Computation Via Neural Networks - Siegelmann, Sontag - 1994
69	Tishby N: The Power of Amnesia - Ron, Singer
66	Variable length markov chains - Buhlmann, Wyner - 1999
63	A universal finite memory source - Weinberger, Rissanen, et al. - 1995
52	Statistical Learning Theory. Wiley-Interscience - Vapnik - 1999
44	Design of a linguistic postprocessor using variable memory length Markov models - Guyon, Pereira - 1995
36	A Self-Organizing Map for Adaptive Processing of Structured Data - Hagenbuchner, Sperduti, et al. - 2003
29	First order recurrent neural networks and deterministic finite state automata. Neural Comput - Manolios, Fanelli - 1994
27	A general framework for unsupervised processing of structured data, Neurocomputing 57 - Hammer, Micheli, et al. - 2004
26	A non-EST-based method for exon-skipping prediction - Sorek, Shemesh, et al. - 2004
24	Dorffner G: Predicting the future of discrete sequences from fractal representations of the past - Tino
23	Markovian architectural bias of recurrent neural networks - Tino, Cernansky, et al. - 2004
23	Recursive Self-Organizing Maps, Neural Networks - Voegtlin - 2002
23	Vapnik-Chervonenkis dimension of recurrent neural networks - Koiran, Sontag - 1998
21	Recurrent networks: state machines or iterated function systems - Kolen - 1994
21	Recurrent neural networks with small weights implement definite memory machines - Hammer, Ti˘no - 2003
21	Recurrent SOM with local linear models in time series prediction - koskela, varsta - 1998
20	Bifurcations in the learning of recurrent neural networks - Doya - 1992
20	Training recurrent networks using the extended kalman filter - Williams - 1992
20	A taxonomy for spatiotemporal connectionist networks revised: the unsupervised case - Kremer, Guilherme, et al.
19	New methods for splice site recognition - Sonnenburg, Rätsch, et al. - 2002
11	N.: Methods for estimating the computational power and generalization capability of neural microcircuits - Maass, Legenstein, et al. - 2005
9	T.: Feedback self-organizing map and its application to spatio-temporal pattern classification - Horio, Yamakawa - 2001
9	On the power of sigmoid neural networks - Kilian, Siegelmann - 1993
9	Recursive self-organizing network models. Neural Networks - Hammer, Micheli, et al. - 2004
9	Bodén M: The applicability of recurrent neural networks for biological sequence analysis - Hawkins
8	Generalization ability of folding networks - Hammer - 2001
7	The origin of clusters in recurrent neural network state space - Kolen - 1994
7	The temporal kohonen map. Neural Networks 6 - Chappell, Taylor - 1993
5	Improved access to sequential motifs: A note on the architectural bias of recurrent networks - Bodén, Hawkins
4	Mourik. Dynamics and topographic organization in recursive self-organizing map - Tiňo, Farkaˇs, et al.
4	C.: Insertion and refinement of production rules in recurrent neural networks - Giles, Omlin
3	New methods for splice site recognition. Master’s thesis, Diplom thesis, Institut für Informatik, Humboldt-Universität Berlin (2002) bias of neural-based architectures with feedback connections 39 - Sonnenburg - 2002