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Bibliografia Avançada de Reconhecimento de Padrões

Abaixo você vai encontrar 80 links "avançados" contendo referências a artigos publicados sobre os mais diversos temas de Reconhecimento de Padrões. Os links foram ordenados pelo CiteSeer por ordem de freqüência de citação (os mais citados no começo). Esta bibliografia não é para quem está iniciando, ela está aqui para você ter mais referências caso você deseje iniciar um trabalho de pesquisa envolvendo Reconhecimento de Padrões.

Todos os links referem-se à cópia dos artigos existente no banco do CiteSeer (http://citeseer.nj.nec.com/). O CiteSeer (Copyright © 1997-2001 NEC Research Institute) é uma máquina de busca para textos científicos com processamento de linguagem natural desenvolvida pela NEC, que automaticamente escaneia um texto encontrado e busca também todas as referências da bibliografia do artigo que puder encontrar. O CiteSeer é sem dúvida o melhor site de busca bibliográfica para trabalhos científicos.

Caso você clique num dos links abaixo e não encontrar mais a referência, simplesmente busque-a novamente através do CiteSeer da seguinte forma: entre no site http://citeseer.nj.nec.com/ e digite ali o nome do artigo que você não encontrou ao clicar no link abaixo. O CiteSeer procurará para você, trazendo-o em PDF, PS, .doc e também trazendo as referências que encontrar.

  1. The Nature of Statistical Learning Theory - Vapnik - 1995
  2. Instance-based learning algorithms - David Aha, Kibler, Albert - 1991
  3. Bagging predictors - Breiman
  4. Bagging predictors - Breiman - 1994
  5. Statistical Learning Theory - Vapnik - 1996
  6. Support-vector networks - Cortes, Vapnik - 1995
  7. Experiments with a new boosting algorithm - Freund, Schapire
  8. A decision-theoretic generalization of on-line learning and an applica.. - Freund, Schapire - 1995
  9. Very simple classification rules perform well on most commonly used da.. - Holte - 1993
  10. The strength of weak learnability - Schapire - 1990
  11. A weighted nearest neighbor algorithm for learning with symbolic featu.. - Cost, Salzberg - 1993
  12. Boosting a weak learning algorithm by majority - Freund - 1995
  13. Multi-interval discretization of continuous-valued attributes in decis.. - Fayyad, Irani - 1993
  14. How to use expert advice - Cesa-Bianchi, Freund, Helmbold et al. - 1993
  15. How to use expert advice - Cesa-Bianchi, Freund, Helmbold et al. - 1996
  16. Fast probabilistic algorithms for Hamiltonian circuits and matchings - Angluin, Valiant - 1979
  17. Supervised and unsupervised discretization of continuous features - Dougherty, Kohavi, Sahami - 1995
  18. A system for the induction of oblique decision trees - Murthy, Kasif, Salzberg - 1994
  19. Adaptive Algorithms and Stochastic Approximations - Benveniste, Metivier, Priouret - 1990
  20. Elements of Machine Learning - Langley - 1996
  21. The context-tree weighting method: Basic properties - Willems, Shtarkov, Tjalkens - 1995
  22. Nearest Neighbor - Dasarathy - 1991
  23. On changing continuous attributes into ordered discrete attributes - Catlett - 1991
  24. A further comparison of splitting rules for decision-tree induction - Buntine, Niblett - 1992
  25. Multivariate decision trees - Brodley, Utgoff - 1995
  26. Discriminant adaptive nearest neighbor classification - Hastie, Tibshirani
  27. The Handbook of Brain Theory and Neural Networks - Arbib - 1995
  28. Similarity metric learning for a variable-kernel classifier - Lowe - 1995
  29. Applications of inductive logic programming - Bratko, Muggleton - 1995
  30. Flexible metric nearest neighbor classification - Friedman - 1994
  31. Connectionist models of face processing: A survey - Valentin, Abdi, O'Toole et al. - 1994
  32. Polynomial splines and their tensor products in extended linear modeli.. - Stone, Hansen, Kooperberg et al. - 1997
  33. Boosting performance in neural networks - Drucker, Schapire, Simard - 1993
  34. Applications of machine learning and rule induction - Langley, Simon - 1995
  35. Boosting decision trees - Drucker, Cortes - 1996
  36. Perceptron trees: a case study in hybrid concept representations - Utgoff - 1989
  37. IEEE Transactions on Pattern Analysis and Machine Intelligence - on, Analysis, Heath et al. - 1993
  38. Using locally weighted regression for robot learning - Atkeson - 1991
  39. Circuit Complexity and Neural Networks - Parberry - 1994
  40. The heuristics of instability in model selection - Breiman
  41. Predicting nearly as well as the best pruning of a decision tree - Helmbold, Schapire - 1996
  42. Decision-theoretic troubleshooting - Heckerman, Breese, Rommelse - 1995
  43. Introduction to Graphical Modelling - Edwards - 1995
  44. Capacity problems for linear machines - Cover - 1968
  45. Robust trainability of single neurons - Hoffgen, Simon, Van Horn - 1995
  46. Improved use of continuous attributes in C - Quinlan
  47. On pruning and averaging decision trees - Oliver, Hand - 1995
  48. Efficient algorithms for finding multi-way splits for decision trees - Fulton, Kasif, Salzberg - 1995
  49. How fast can a threshold gate learn - Maass, Turan - 1994
  50. Smoothing spline anova for exponential families - Wahba, Wang, Gu et al. - 1996
  51. line prediction and boosting - Freund, Schapire
  52. Polychotomous regression - Kooperberg, Bose, Stone - 1996
  53. variance and arcing classifiers - Breiman
  54. Polynomial bounds for VC dimension of sigmoidal neural networks - Karpinski, Macintyre
  55. Structure and chance: Melding logic and probability for software debug.. - Burnell, Horvitz - 1995
  56. Tighter bounds of the VC-dimension of three-layer networks - Sakurai - 1993
  57. Multiple binary decision tree classifiers - Shlien - 1990
  58. Applying Bayesian networks to information retrival - Fung, Del - 1995
  59. OC1: randomized induction of oblique decision tress - Murthy, Kasif, Salzberg et al. - 1993
  60. Theory of majority decision elements - Muroga, Toda, Takasu - 1961
  61. Towards a better understanding of memory-based and Bayesian classifier.. - Rachlin, Kasif, Salzberg et al. - 1994
  62. Probabilistic Expert Systems - Shafer - 1996
  63. Memory-based reasoning - Waltz - 1990
  64. Flat minima - Hochreiter, Schmidhuber - 1996
  65. Bayesian networks - Heckerman, Wellman - 1995
  66. Backpropagation: Basics and new developments - Werbos - 1995
  67. Simplifying neural nets by discovering flat minima - Hochreiter, Schmidhuber - 1995
  68. Vapnik-Chervonenkis bounds for generalization - Parrondo, Van der Broeck - 1993
  69. Finding optimal multi-splits for numerical attributes in decision tree.. - Elomaa, Rousu - 1996
  70. Context tree weighting: A sequential universal source coding procedure.. - Willems, Shtarkov, Tjalkens - 1993
  71. Stochastic Approximation and Optimization of Random Systems - Ljung, Pflug, Walk - 1992
  72. The VC dimension and pseudodimension of two-layer neural networks with.. - Bartlett, Williamson - 1996
  73. A new nearest neighbor distance measure - Short, Fukunaga - 1980
  74. Random decision forests - Ho - 1995
  75. Lower bounds of the number of threshold functions and a maximum weight - Muroga - 1965
  76. Fast decision tree ensembles for optical character recognition - Drucker - 1996
  77. Parallel Digital Implementation of Neural Networks - Phys, --, Prasanna - 1993
  78. Predicting nearly as well as the best pruning of a decision tree - the, --, Schapire - 1995
  79. Learning how the world works - Werbos - 1987
  80. Linear function neurons: structure and training - the, --, Volper - 1986
 
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