Articles

1. E. Vidal, F. Thollard, C. de la Higuera, , F. Casacuberta, and R. C. Carrasco. Probabilistic finite-state machines - Part I. IEEE Trans. on Pattern analysis and Machine Intelligence, 27(7):1013-1025, 2005.
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   In part I of this paper we survey probabilistic finite-state machines as generative objects and study their definitions and properties.

2. E. Vidal, F. Thollard, C. de la Higuera, , F. Casacuberta, and R. C. Carrasco. Probabilistic finite-state machines - Part II. IEEE Trans. on Pattern analysis and Machine Intelligence, 27(7):1026-1039, 2005.
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   In part II, we study the relation of probabilistic finite-state automata with other well known devices that generate strings as hidden Markov models and n-grams, and provide theorems, algorithms and properties that represent a current state of the art of these objects.

3. Jose Luis Verdú-Mas, Rafael C. Carrasco, and Jorge Calera-Rubio. Parsing with probabilistic strictly locally testable tree languages. IEEE Trans. on Pattern analysis and Machine Intelligence, 27(7):1040-1050, 2005.
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   We introduce the family of stochastic k-testable tree languages and describe how these models can approximate any stochastic rational tree language. The model is applied to the task of learning a probabilistic k-testable model from a sample of parsed sentences. In particular, a parser for a natural language grammar that incorporates smoothing is shown.

4. Juan Ramón Rico-Juan, Jorge Calera-Rubio, and Rafael C. Carrasco. Smoothing and compression with stochastic k-testable tree languages. Pattern Recognition, 38(9):1420-1430, 2005.
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   In this paper, we describe some techniques to learn probabilistic k-testable tree models, a generalization of the well known k-gram models, that can be used to compress or classify structured data.

5. Rafael C. Carrasco and Juan Ramón Rico-Juan. A similarity between probabilistic tree languages: application to XML document families. Pattern Recognition, 36(9):2197-2199, 2003.
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   We describe a general approach to compute a similarity measure between distributions generated by probabilistic tree automata. We show how this similarity can be computed for families of structured (XML) documents.

6. Rafael C. Carrasco and Mikel L. Forcada. Incremental construction and maintenance of minimal finite-state automata. Computational Linguistics, 28(2):207-216, 2002.
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   We describe a simple and efficient method to modify any minimal finite-state automaton (acyclic or not) so that a string is added to or removed from the language accepted by it; both operations solve the dictionary construction problem addressed by Daciuk et al. as a special case.

7. Rafael C. Carrasco, Jose Oncina, and Jorge Calera-Rubio. Stochastic inference of regular tree languages. Machine Learning, 44(1/2):185-197, 2001.
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   We generalize a former algorithm for regular language identification from stochastic samples to the case of tree languages. The algorithm is used to identify context-free languages when structural information about the strings is available.

8. Rafael C. Carrasco and Mikel L. Forcada. Simple strategies to encode tree automata in sigmoid tree-walking neural networks. IEEE Transactions on Knowledge and Data Engineering, 13(2):148-156, 2001.
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   In this paper, we explore the simulation of deterministic finite-state tree automata DFSTA in sigmoid tree-walking neural nets TWNN (that is, analog TWNN using monotonously growing transfer functions), and also present an alternative scheme for one-hot encoding of the input that yields smaller weight values and therefore works at a lower saturation level.

9. Rafael C. Carrasco, Mikel L. Forcada, M. Ángeles Valdés-Muñoz, and Ramón P. Ñeco. Stable encoding of finite-state machines in discrete-time recurrent neural nets with sigmoid units. Neural Computation, 12(9):2129-2174, 2000.
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   Unlike previous work that either imposed some restrictions to state values, or used a detailed analysis based on fixed-point attractors, we present an approach which applies to any positive, bounded, strictly growing, continuous activation function, and uses simple bounding criteria based on a study of the conditions under which a proposed encoding scheme guarantees that the DTRNN is actually behaving as a finite-state machine.

10. Rafael C. Carrasco and Jose Oncina. Learning deterministic regular grammars from stochastic samples in polynomial time. RAIRO (Theoretical Informatics and Applications), 33(1):1-20, 1999.
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    We propose a class of algorithms for the identification of stochastic regular languages which allow for the identification of the structure of the minimal stochastic automaton generating the language. It is shown that the time needed grows only linearly with the size of the sample set.

11. Jorge Calera-Rubio and Rafael C. Carrasco. Computing the relative entropy between regular tree languages. Information Processing Letters, 68(6):283-289, 1998.
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    Grammatical inference methods are often checked with training samples generated by a known grammar which is later compared to the grammar inferred from the sample. We describe an efficient procedure to compute the relative entropy between two stochastic deterministic regular tree grammars.

12. Rafael C. Carrasco. Accurate computation of the relative entropy between stochastic regular grammars. RAIRO (Theoretical Informatics and Applications), 31(5):437-444, 1997.
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    Usually, grammatical inference methods use large test sets generated with the true distribution to evaluate the relative entropy between the model and the true gramamr. In this paper, an iterative procedure to compute the relative entropy between two stochastic deterministic regular grammars is proposed.

13. Luisa Micó, Jose Oncina, and Rafael C. Carrasco. A fast branch and bound nearest neighbour classifier in metric spaces. Pattern Recognition Letters, 17(5):731-739, 1996.
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    The recently introduced algorithm LAESA finds the nearest neighbour prototype in a metric space. The average number of distances computed in the algorithm does not depend on the number of prototypes but it shows linear space and time complexities. In this paper, a new algorithm (TLAESA) is proposed which has a sublinear time complexity and keeps the other features unchanged.

14. Mikel L. Forcada and Rafael C. Carrasco. Learning the initial state of a second-order recurrent neural network during regular-language inference. Neural Computation, 7(5):923-930, 1995.
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    A modified version of the real-time recurrent learning (RTRL) algorithm used to train 2ORNNs, than learns the initial state in addition to the weights improves the learning of regular languages when the size of the network is small.

15. Rafael C. Carrasco and Mikel L. Forcada. A note on the Nagendraprasad-Wang-Gupta thinning algorithm. Pattern Recognition Letters, 16(5):539-541, 1995.
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    A symmetrized version of the Nagendraprasad-Wang-Gupta thinning algorithm produces simpler and more elegant skeletons of handwritten characters at zero extra computational cost.

16. R. C. Carrasco. Nuclear Compton scattering in the delta resonance region. Anales de Física, 90:8-16, 1994.
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    The resonant amplitude and the imaginary part of the Compton amplitude are calculated using microscopic many body methods. The real part of the background is computed using dispersion relations.

17. R. C. Carrasco, M. J. Vicente Vacas, and E. Oset. Inclusive (gamma, n), (gamma, n n) and (gamma, n pi) reactions in nuclei at intermediate-energies. Nucl. Phys., A570:701-721, 1994.
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    Differential cross sections of nucleons excited in photonuclear reactions are studied by considering all relevant reaction mechanisms. Also cross sections for nucleon emission in coincidence with one pion are calculated.

18. R. C. Carrasco. Inclusive eta photoproduction in nuclei. Phys. Rev., C48:2333-2339, 1993.
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    A local model for the nuclear modifications to the photoproduction of eta mesons through the N*(1535) resonance predicts that the cross section for different nuclei behaves like A^alpha whith alpha approximately 0.6

19. J. Nieves, E. Oset, and R. C. Carrasco. Deeply bound pionic atoms with resonant compton scattering. Nucl. Phys., A565:785-796, 1993.
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    We study the contribution to the Compton nuclear scattering of the resonant channel (A'pi-) when a negative charge pion is bound in the nucleus

20. R. C. Carrasco, J.M. Nieves, and E. Oset. Coherent (gamma, pi0) photoproduction in a local approximation to the Delta-hole model. Nucl. Phys., A565:797-817, 1993.
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    We develop a local approximation to the Delta-hole model for coherent pi0 photoproduction and apply it to the calculation of cross sections in heavy nuclei, where traditional approaches are unfeasible

21. R. C. Carrasco, L.L. Salcedo, and E. Oset. Inclusive (gamma, pi) reactions in nuclei. Nucl. Phys., A541:585-622, 1992.
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    Double differential cross sections for inclusive (gamma,pi) reactions in nuclei are computed using a microscopic approach based on local models and many body quantum theory. All relevant mechanism and final state interactions are taken into account.

22. R. C. Carrasco and E. Oset. Interaction of real photons with nuclei from 100-MEV to 500-MEV. Nucl. Phys., A536:445-588, 1992.
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    A systematic many body expansion in the number of particle-hole excitations is developed. We use effective model for the basic interactions and local models to take into account the nuclear medium effect.

23. R. C. Carrasco and E. Oset. Enhancement of the nuclear dipole sum rule: a microscopic approach. Phys. Rev., C45:764-770, 1992.
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    The use of local models to study the nuclear dipole sum rule allows one to separate different contributions o this magnitude. This provides us with a deeper insight of this sum rule.

24. H. C. Chiang, E. Oset, R. C. Carrasco, J. M. Nieves, and J. Navarro. Inclusive radiative pion capture in nuclei. Nucl. Phys., A510:573-590, 1990.
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    The problem of inclusive radiative pion capture in nuclei is reanalyzed from a many body point of view.