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Richard Nock: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Svetlana Kiritchenko, Stan Matwin, Richard Nock, A. Fazel Famili
    Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2006, pp:395-406 [Conf]
  2. Richard Nock, Babak Esfandiari
    Oracles and Assistants: Machine Learning Applied to Network Supervision. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1998, pp:86-98 [Conf]
  3. Marc Sebban, Richard Nock
    Identifying and Eliminating Irrelevant Instances Using Information Theory. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2000, pp:90-101 [Conf]
  4. Richard Nock
    Complexity in the Case against Accuracy: When Building one Function-Free Horn Clause is as Hard as Any. [Citation Graph (0, 0)][DBLP]
    ATL, 1999, pp:182-193 [Conf]
  5. Richard Nock, Marc Sebban
    Sharper Bounds for the Hardness of Prototype and Feature Selection. [Citation Graph (0, 0)][DBLP]
    ALT, 2000, pp:224-237 [Conf]
  6. Christophe Fiorio, Richard Nock
    A Concentration-Based Adaptive Approach to Region Merging of Optimal Time and Space Complexities. [Citation Graph (0, 0)][DBLP]
    BMVC, 2000, pp:- [Conf]
  7. Frank Nielsen, Richard Nock
    Approximating smallest enclosing disks. [Citation Graph (0, 0)][DBLP]
    CCCG, 2004, pp:124-127 [Conf]
  8. Pierre-Alain Laur, Richard Nock, Jean-Emile Symphor, Pascal Poncelet
    On the estimation of frequent itemsets for data streams: theory and experiments. [Citation Graph (0, 0)][DBLP]
    CIKM, 2005, pp:327-328 [Conf]
  9. Frank Nielsen, Richard Nock
    On approximating the smallest enclosing Bregman Balls. [Citation Graph (0, 0)][DBLP]
    Symposium on Computational Geometry, 2006, pp:485-486 [Conf]
  10. Frank Nielsen, Jean-Daniel Boissonnat, Richard Nock
    Visualizing bregman voronoi diagrams. [Citation Graph (0, 0)][DBLP]
    Symposium on Computational Geometry, 2007, pp:121-122 [Conf]
  11. Frank Nielsen, Richard Nock
    On Region Merging: The Statistical Soundness of Fast Sorting, with Applications. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2003, pp:19-26 [Conf]
  12. Frank Nielsen, Richard Nock
    Interactive Pinpoint Image Object Removal. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2005, pp:1191- [Conf]
  13. Richard Nock
    Fast and Reliable Color Region Merging inspired by Decision Tree Pruning. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2001, pp:271-0 [Conf]
  14. Richard Nock, Frank Nielsen
    Grouping with Bias Revisited. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2004, pp:460-465 [Conf]
  15. Richard Nock, Frank Nielsen
    A Real Generalization of Discrete AdaBoost. [Citation Graph (0, 0)][DBLP]
    ECAI, 2006, pp:509-515 [Conf]
  16. Richard Nock, Pascal Vaillant, Frank Nielsen, Claudia Henry
    Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm. [Citation Graph (0, 0)][DBLP]
    ECAI, 2006, pp:823-824 [Conf]
  17. Richard Nock, Patrice Lefaucheur
    A Robust Boosting Algorithm. [Citation Graph (0, 0)][DBLP]
    ECML, 2002, pp:319-330 [Conf]
  18. Richard Nock, Frank Nielsen
    Fitting the Smallest Enclosing Bregman Ball. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:649-656 [Conf]
  19. Richard Nock, Marc Sebban, Pascal Jabby
    A Symmetric Nearest Neighbor Learning Rule. [Citation Graph (0, 0)][DBLP]
    EWCBR, 2000, pp:222-233 [Conf]
  20. Richard Nock, Marc Sebban
    A Boosting-Based Prototype Weighting and Selection Scheme. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2000, pp:71-75 [Conf]
  21. Marc Sebban, Richard Nock
    Improvement of Nearest-Neighbor Classifiers via Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2001, pp:113-117 [Conf]
  22. Pascal Jappy, Richard Nock
    PAC Learning Conceptual Graphs. [Citation Graph (0, 0)][DBLP]
    ICCS, 1998, pp:303-318 [Conf]
  23. Frank Nielsen, Richard Nock
    Approximating Smallest Enclosing Balls. [Citation Graph (0, 0)][DBLP]
    ICCSA (3), 2004, pp:147-157 [Conf]
  24. Frank Nielsen, Richard Nock
    Interactive Point-and-Click Segmentation for Object Removal in Digital Images. [Citation Graph (0, 0)][DBLP]
    ICCV-HCI, 2005, pp:131-140 [Conf]
  25. Christophe Fiorio, Richard Nock
    Sorted Region Merging to Maximize Test Reliability. [Citation Graph (0, 0)][DBLP]
    ICIP, 2000, pp:- [Conf]
  26. Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier
    Boosting grammatical inference with confidence oracles. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  27. Pascal Jappy, Richard Nock, Olivier Gascuel
    Negative Robust Learning Results from Horn Claus Programs. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:258-265 [Conf]
  28. Richard Nock, Olivier Gascuel
    On Learning Decision Committees. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:413-420 [Conf]
  29. Richard Nock, Pascal Jappy
    On the Power of Decision Lists. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:413-420 [Conf]
  30. Marc Sebban, Richard Nock
    Instance Pruning as an Information Preserving Problem. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:855-862 [Conf]
  31. Marc Sebban, Richard Nock, Stéphane Lallich
    Boosting Neighborhood-Based Classifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:505-512 [Conf]
  32. Patrice Lefaucheur, Richard Nock
    Robust Multiclass Ensemble Classifiers via Symmetric Functions. [Citation Graph (0, 0)][DBLP]
    ICPR (4), 2006, pp:136-139 [Conf]
  33. Richard Nock, Pierre-Alain Laur, Jean-Emile Symphor
    Statistical Borders for Incremental Mining. [Citation Graph (0, 0)][DBLP]
    ICPR (3), 2006, pp:212-215 [Conf]
  34. Richard Nock, Frank Nielsen
    Improving Clustering Algorithms through Constrained Convex Optimization. [Citation Graph (0, 0)][DBLP]
    ICPR (4), 2004, pp:557-560 [Conf]
  35. Richard Nock, Vincent Pagé
    Grouping with Bias for Distribution-Free Mixture Model Estimation. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2004, pp:44-47 [Conf]
  36. Richard Nock, Pascal Jappy
    A ``Top-Down and Prune'' Induction Scheme for Constrained Decision Committees. [Citation Graph (0, 0)][DBLP]
    IDA, 1999, pp:27-38 [Conf]
  37. Claudia Henry, Richard Nock, Frank Nielsen
    Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:842-847 [Conf]
  38. Richard Nock, Pascal Jappy
    Function-Free Horn Clauses Are Hard to Approximate. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:195-204 [Conf]
  39. Richard Nock, Pascal Jappy, Jean Sallantin
    Generalized Graph Colorability and Compressibility of Boolean Formulae. [Citation Graph (0, 0)][DBLP]
    ISAAC, 1998, pp:237-246 [Conf]
  40. Pierre-Alain Laur, Jean-Emile Symphor, Richard Nock, Pascal Poncelet
    Statistical Supports for Frequent Itemsets on Data Streams. [Citation Graph (0, 0)][DBLP]
    MLDM, 2005, pp:395-404 [Conf]
  41. Frank Nielsen, Richard Nock
    ClickRemoval: interactive pinpoint image object removal. [Citation Graph (0, 0)][DBLP]
    ACM Multimedia, 2005, pp:315-318 [Conf]
  42. Richard Nock, Babak Esfandiari
    On-Line Adaptive Filtering of Web Pages. [Citation Graph (0, 0)][DBLP]
    PKDD, 2005, pp:634-642 [Conf]
  43. Richard Nock, Marc Sebban, Pascal Jappy
    Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:223-231 [Conf]
  44. Marc Sebban, Richard Nock
    Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:44-53 [Conf]
  45. Marc Sebban, Richard Nock
    Contribution of Boosting in Wrapper Models. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:214-222 [Conf]
  46. Richard Nock, Frank Nielsen
    An Abstract Weighting Framework for Clustering Algorithms. [Citation Graph (0, 0)][DBLP]
    SDM, 2004, pp:- [Conf]
  47. Marc Sebban, Richard Nock
    Combining Feature and Example Pruning by Uncertainty Minimization. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:533-540 [Conf]
  48. Babak Esfandiari, Richard Nock
    Adaptive filtering of advertisements on web pages. [Citation Graph (0, 0)][DBLP]
    WWW (Special interest tracks and posters), 2005, pp:916-917 [Conf]
  49. Richard Nock, Frank Nielsen
    A Real generalization of discrete AdaBoost. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2007, v:171, n:1, pp:25-41 [Journal]
  50. Richard Nock, Pascal Jappy
    Decision tree based induction of decision lists. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 1999, v:3, n:3, pp:227-240 [Journal]
  51. Pierre-Alain Laur, Jean-Emile Symphor, Richard Nock, Pascal Poncelet
    Statistical supports for mining sequential patterns and improving the incremental update process on data streams. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2007, v:11, n:1, pp:29-47 [Journal]
  52. Richard Nock, Marc Sebban
    Advances in Adaptive Prototype Weighting and Selection. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2001, v:10, n:1-2, pp:137-155 [Journal]
  53. Marc Sebban, Richard Nock, Jean-Hugues Chauchat, Ricco Rakotomalala
    Impact of learning set quality and size on decision tree performances. [Citation Graph (0, 0)][DBLP]
    Int. J. Comput. Syst. Signal, 2000, v:1, n:1, pp:85-105 [Journal]
  54. Olivier Gascuel, Bernadette Bouchon-Meunier, Gilles Caraux, Patrick Gallinari, Alain Guénoche, Yann Guermeur, Yves Lechevallier, Christophe Marsala, Laurent Miclet, Jacques Nicolas, Richard Nock, Mohammed Ramdani, Michèle Sebag, Basavanneppa Tallur, Gilles Venturini, Patrick Vitte
    Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 1998, v:12, n:4, pp:517-571 [Journal]
  55. Richard Nock, Marc Sebban, Didier Bernard
    A Simple Locally Adaptive Nearest Neighbor Rule With Application To Pollution Forecasting. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 2003, v:17, n:8, pp:1369-1382 [Journal]
  56. Frank Nielsen, Richard Nock
    A fast deterministic smallest enclosing disk approximation algorithm. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 2005, v:93, n:6, pp:263-268 [Journal]
  57. Richard Nock, Tapio Elomaa, Matti Kääriäinen
    Reduced Error Pruning of branching programs cannot be approximated to within a logarithmic factor. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 2003, v:87, n:2, pp:73-78 [Journal]
  58. Richard Nock
    Inducing Interpretable Voting Classifiers without Trading Accuracy for Simplicity: Theoretical Results, Approximation Algorithms, and Experiments. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2002, v:17, n:, pp:137-170 [Journal]
  59. Marc Sebban, Richard Nock, Stéphane Lallich
    Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:863-885 [Journal]
  60. Richard Nock, Frank Nielsen
    Statistical Region Merging. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2004, v:26, n:11, pp:1452-1458 [Journal]
  61. Richard Nock, Frank Nielsen
    On Weighting Clustering. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2006, v:28, n:8, pp:1223-1235 [Journal]
  62. Richard Nock, Frank Nielsen
    Semi-supervised statistical region refinement for color image segmentation. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2005, v:38, n:6, pp:835-846 [Journal]
  63. Marc Sebban, Richard Nock
    A hybrid filter/wrapper approach of feature selection using information theory. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2002, v:35, n:4, pp:835-846 [Journal]
  64. Pierre-Alain Laur, Richard Nock, Jean-Emile Symphor, Pascal Poncelet
    Mining evolving data streams for frequent patterns. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2007, v:40, n:2, pp:492-503 [Journal]
  65. Richard Nock, Marc Sebban
    An improved bound on the finite-sample risk of the nearest neighbor rule. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2001, v:22, n:3/4, pp:407-412 [Journal]
  66. Richard Nock, Marc Sebban
    A Bayesian boosting theorem. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2001, v:22, n:3/4, pp:413-419 [Journal]
  67. Richard Nock
    Complexity in the case against accuracy estimation. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2003, v:1, n:301, pp:143-165 [Journal]
  68. Richard Nock, Frank Nielsen
    On domain-partitioning induction criteria: worst-case bounds for the worst-case based. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2004, v:321, n:2-3, pp:371-382 [Journal]
  69. Richard Nock, Frank Nielsen
    Self-improved gaps almost everywhere for the agnostic approximation of monomials. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2007, v:377, n:1-3, pp:139-150 [Journal]
  70. Frank Nielsen, Richard Nock
    On the Smallest Enclosing Information Disk. [Citation Graph (0, 0)][DBLP]
    CCCG, 2006, pp:- [Conf]
  71. Frank Nielsen, Jean-Daniel Boissonnat, Richard Nock
    On Bregman Voronoi diagrams. [Citation Graph (0, 0)][DBLP]
    SODA, 2007, pp:746-755 [Conf]
  72. Frank Nielsen, Jean-Daniel Boissonnat, Richard Nock
    Bregman Voronoi Diagrams: Properties, Algorithms and Applications [Citation Graph (0, 0)][DBLP]
    CoRR, 2007, v:0, n:, pp:- [Journal]

  73. Levels of Details for Gaussian Mixture Models. [Citation Graph (, )][DBLP]


  74. On the efficient minimization of convex surrogates in supervised learning. [Citation Graph (, )][DBLP]


  75. Bregman sided and symmetrized centroids. [Citation Graph (, )][DBLP]


  76. On the Efficient Minimization of Classification Calibrated Surrogates. [Citation Graph (, )][DBLP]


  77. Mixed Bregman Clustering with Approximation Guarantees. [Citation Graph (, )][DBLP]


  78. Jensen-Bregman Voronoi Diagrams and Centroidal Tessellations. [Citation Graph (, )][DBLP]


  79. The Dual Voronoi Diagrams with Respect to Representational Bregman Divergences. [Citation Graph (, )][DBLP]


  80. Fast Graph Segmentation Based on Statistical Aggregation Phenomena. [Citation Graph (, )][DBLP]


  81. Intrinsic Geometries in Learning. [Citation Graph (, )][DBLP]


  82. Clustering Multivariate Normal Distributions. [Citation Graph (, )][DBLP]


  83. On the Centroids of Symmetrized Bregman Divergences [Citation Graph (, )][DBLP]


  84. Staring at Economic Aggregators through Information Lenses [Citation Graph (, )][DBLP]


  85. Analyse spectrale des textes: détection automatique des frontières de langue et de discours [Citation Graph (, )][DBLP]


  86. Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm [Citation Graph (, )][DBLP]


  87. Information geometries and Microeconomic Theories [Citation Graph (, )][DBLP]


  88. Hyperbolic Voronoi diagrams made easy [Citation Graph (, )][DBLP]


  89. Boosting k-NN for categorization of natural scenes [Citation Graph (, )][DBLP]


  90. Bregman Voronoi Diagrams. [Citation Graph (, )][DBLP]


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