The SCEAS System
Navigation Menu

Search the dblp DataBase

Title:
Author:

Joachim M. Buhmann: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Lothar Hermes, Joachim M. Buhmann
    Contextual Classification by Entropy-Based Polygonization. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2001, pp:442-447 [Conf]
  2. Tilman Lange, Martin H. C. Law, Anil K. Jain, Joachim M. Buhmann
    Learning with Constrained and Unlabelled Data. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2005, pp:731-738 [Conf]
  3. Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
    Histogram Clustering for Unsupervised Image Segmentation. [Citation Graph (0, 0)][DBLP]
    CVPR, 1999, pp:2602-2608 [Conf]
  4. Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann
    Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval. [Citation Graph (0, 0)][DBLP]
    CVPR, 1997, pp:267-272 [Conf]
  5. Andrew Rabinovich, Serge Belongie, Tilman Lange, Joachim M. Buhmann
    Model Order Selection and Cue Combination for Image Segmentation. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2006, pp:1130-1137 [Conf]
  6. Thomas Zöller, Joachim M. Buhmann
    Shape Constrained Image Segmentation by Parametric Distributional Clustering. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2004, pp:386-393 [Conf]
  7. Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
    Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2006, pp:344-353 [Conf]
  8. Wei-Jun Chen, Joachim M. Buhmann
    A New Distance Measure for Probabilistic Shape Modeling. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2003, pp:507-514 [Conf]
  9. Bernd Fischer, Joachim M. Buhmann
    Data Resampling for Path Based Clustering. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2002, pp:206-214 [Conf]
  10. Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
    Discrete Mixture Models for Unsupervised Image Segmentation. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1998, pp:135-142 [Conf]
  11. Hansruedi Peter, Bernd Fischer, Joachim M. Buhmann
    Probabilistic De Novo Peptide Sequencing with Doubly Charged Ions. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2006, pp:424-433 [Conf]
  12. Markus Suing, Lothar Hermes, Joachim M. Buhmann
    A New Contour-Based Approach to Object Recognition for Assembly Line Robots. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2001, pp:329-336 [Conf]
  13. Peter Wey, Bernd Fischer, Herbert Bay, Joachim M. Buhmann
    Dense Stereo by Triangular Meshing and Cross Validation. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2006, pp:708-717 [Conf]
  14. Joachim M. Buhmann, Hans Kühnel
    Complexity Optimized Vector Quantization: A Neutral Network Approach. [Citation Graph (0, 0)][DBLP]
    Data Compression Conference, 1992, pp:12-21 [Conf]
  15. Lothar Hermes, Thomas Zöller, Joachim M. Buhmann
    Parametric Distributional Clustering for Image Segmentation. [Citation Graph (0, 0)][DBLP]
    ECCV (3), 2002, pp:577-591 [Conf]
  16. Jens Ketterer, Jan Puzicha, Marcus Held, Martin Fischer, Joachim M. Buhmann, Dieter W. Fellner
    On Spatial Quantization of Color Images. [Citation Graph (0, 0)][DBLP]
    ECCV (1), 1998, pp:563-577 [Conf]
  17. Björn Ommer, Joachim M. Buhmann
    Learning Compositional Categorization Models. [Citation Graph (0, 0)][DBLP]
    ECCV (3), 2006, pp:316-329 [Conf]
  18. Peter Orbanz, Joachim M. Buhmann
    Smooth Image Segmentation by Nonparametric Bayesian Inference. [Citation Graph (0, 0)][DBLP]
    ECCV (1), 2006, pp:444-457 [Conf]
  19. Hansjörg Klock, Joachim M. Buhmann
    Multidimensional Scaling by Deterministic Annealing. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 1997, pp:245-260 [Conf]
  20. Björn Ommer, Joachim M. Buhmann
    A Compositionally Architecture for Perceptual Feature Grouping. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2003, pp:275-290 [Conf]
  21. Björn Ommer, Joachim M. Buhmann
    Object Categorization by Compositional Graphical Models. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2005, pp:235-250 [Conf]
  22. Bernd Fischer, Thomas Zöller, Joachim M. Buhmann
    Path Based Pairwise Data Clustering with Application to Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2001, pp:235-250 [Conf]
  23. Lothar Hermes, Joachim M. Buhmann
    Semi-supervised Image Segmentation by Parametric Distributional Clustering. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2003, pp:229-245 [Conf]
  24. Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    Deterministic Annealing for Unsupervised Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 1997, pp:213-228 [Conf]
  25. Thomas Hofmann, Joachim M. Buhmann
    An Annealed ``Neural Gas'' Network for Robust Vector Quantization. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:151-156 [Conf]
  26. Volker Roth, Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
    Stability-Based Model Order Selection in Clustering with Applications to Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:607-612 [Conf]
  27. Jan Puzicha, Joachim M. Buhmann
    Multiscale Annealing for Real-Time Unsupervised Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    ICCV, 1998, pp:267-273 [Conf]
  28. Jan Puzicha, Yossi Rubner, Carlo Tomasi, Joachim M. Buhmann
    Empirical Evaluation of Dissimilarity Measures for Color and Texture. [Citation Graph (0, 0)][DBLP]
    ICCV, 1999, pp:1165-1172 [Conf]
  29. Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios, Frans Coetzee, Joachim M. Buhmann
    Topology Free Hidden Markov Models: Application to Background Modeling. [Citation Graph (0, 0)][DBLP]
    ICCV, 2001, pp:294-301 [Conf]
  30. Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    An Optimization Approach to Unsupervised Hierarchical Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    ICIP (3), 1997, pp:213-216 [Conf]
  31. Hansjörg Klock, Andreas Polzer, Joachim M. Buhmann
    Region-Based Motion Compensated 3D-Wavelet Transform Coding of Video. [Citation Graph (0, 0)][DBLP]
    ICIP (2), 1997, pp:776-779 [Conf]
  32. Andreas Polzer, Hansjörg Klock, Joachim M. Buhmann
    Video coding by region-based motion compensation and spatio-temporal wavelet transform. [Citation Graph (0, 0)][DBLP]
    ICIP (3), 1997, pp:436-439 [Conf]
  33. Stefan Will, Lothar Hermes, Joachim M. Buhmann, Jan Puzicha
    On Learning Optimal Texture Edge Detectors. [Citation Graph (0, 0)][DBLP]
    ICIP, 2000, pp:- [Conf]
  34. Peter Orbanz, Joachim M. Buhmann
    SAR images as mixtures of Gaussian mixtures. [Citation Graph (0, 0)][DBLP]
    ICIP (2), 2005, pp:209-212 [Conf]
  35. Zvika Marx, Ido Dagan, Joachim M. Buhmann
    Coupled Clustering: a Method for Detecting Structural Correspondence. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:353-360 [Conf]
  36. Joachim M. Buhmann, Thomas Zöller
    Active Learning for Hierarchical Pairwise Data Clustering. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:2186-2189 [Conf]
  37. Lothar Hermes, Joachim M. Buhmann
    Feature Selection for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:2712-2715 [Conf]
  38. Anil K. Jain, Alexander P. Topchy, Martin H. C. Law, Joachim M. Buhmann
    Landscape of Clustering Algorithms. [Citation Graph (0, 0)][DBLP]
    ICPR (1), 2004, pp:260-263 [Conf]
  39. Thomas Zöller, Lothar Hermes, Joachim M. Buhmann
    Combined Color And Texture Segmentation by Parametric Distributional Clustering. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2002, pp:627-630 [Conf]
  40. Bernd Fischer, Jonas Grossmann, Volker Roth, Wilhelm Gruissem, Sacha Baginsky, Joachim M. Buhmann
    Semi-supervised LC/MS alignment for differential proteomics. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2006, pp:132-140 [Conf]
  41. Thomas Hofmann, Joachim M. Buhmann
    Inferring Hierarchical Clustering Structures by Deterministic Annealing. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:363-366 [Conf]
  42. Tilman Lange, Joachim M. Buhmann
    Combining partitions by probabilistic label aggregation. [Citation Graph (0, 0)][DBLP]
    KDD, 2005, pp:147-156 [Conf]
  43. Mikio L. Braun, Joachim M. Buhmann
    The Noisy Euclidean Traveling Salesman Problem and Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:351-358 [Conf]
  44. Joachim M. Buhmann, Thomas Hofmann
    Central and Pairwise Data Clustering by Competitive Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:104-111 [Conf]
  45. Joachim M. Buhmann, Marcus Held
    Model Selection in Clustering by Uniform Convergence Bounds. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:216-222 [Conf]
  46. Joachim M. Buhmann, Martin Lades, Frank H. Eeckman
    Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:769-776 [Conf]
  47. Bernd Fischer, Volker Roth, Joachim M. Buhmann
    Clustering with the Connectivity Kernel. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  48. Bernd Fischer, Volker Roth, Joachim M. Buhmann, Jonas Grossmann, Sacha Baginsky, Wilhelm Gruissem, Franz Roos, Peter Widmayer
    A Hidden Markov Model for de Novo Peptide Sequencing. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  49. Marcus Held, Joachim M. Buhmann
    Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  50. Marcus Held, Jan Puzicha, Joachim M. Buhmann
    Visualizing Group Structure. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:452-458 [Conf]
  51. Thomas Hofmann, Joachim M. Buhmann
    Multidimensional Scaling and Data Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:459-466 [Conf]
  52. Thomas Hofmann, Joachim M. Buhmann
    Active Data Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  53. Tilman Lange, Joachim M. Buhmann
    Fusion of Similarity Data in Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  54. Tilman Lange, Mikio L. Braun, Volker Roth, Joachim M. Buhmann
    Stability-Based Model Selection. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:617-624 [Conf]
  55. Volker Roth, Julian Laub, Joachim M. Buhmann, Klaus-Robert Müller
    Going Metric: Denoising Pairwise Data. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:817-824 [Conf]
  56. Joachim M. Buhmann
    Clustering in Computer Vision and Data Analysis. [Citation Graph (0, 0)][DBLP]
    PRIS, 2004, pp:3- [Conf]
  57. Joachim M. Buhmann, Jan Puzicha
    Unsupervised Learning for Robust Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    Theoretical Foundations of Computer Vision, 1998, pp:195-209 [Conf]
  58. Joachim M. Buhmann, Wolfram Burgard, Armin B. Cremers, Dieter Fox, Thomas Hofmann, Frank E. Schneider, Jiannis Strikos, Sebastian Thrun
    The Mobile Robot RHINO. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 1995, v:16, n:2, pp:31-38 [Journal]
  59. Joachim M. Buhmann, Dieter W. Fellner, Marcus Held, Jens Ketterer, Jan Puzicha
    Dithered Color Quantization. [Citation Graph (0, 0)][DBLP]
    Comput. Graph. Forum, 1998, v:17, n:3, pp:219-232 [Journal]
  60. Zvika Marx, Ido Dagan, Joachim M. Buhmann
    Coupled Clustering: a Method for Detecting Structural Correspondence [Citation Graph (0, 0)][DBLP]
    CoRR, 2001, v:0, n:, pp:- [Journal]
  61. Jan Puzicha, Joachim M. Buhmann
    Multiscale Annealing for Grouping and Unsupervised Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    Computer Vision and Image Understanding, 1999, v:76, n:3, pp:213-230 [Journal]
  62. Yossi Rubner, Jan Puzicha, Carlo Tomasi, Joachim M. Buhmann
    Empirical Evaluation of Dissimilarity Measures for Color and Texture. [Citation Graph (0, 0)][DBLP]
    Computer Vision and Image Understanding, 2001, v:84, n:1, pp:25-43 [Journal]
  63. Zvika Marx, Ido Dagan, Joachim M. Buhmann, Eli Shamir
    Coupled Clustering: A Method for Detecting Structural Correspondence. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:747-780 [Journal]
  64. Joachim M. Buhmann
    Knowledge-Discovery: Wie können wir Muster und Strukturen in Daten zuverlässig erkennen? [Citation Graph (0, 0)][DBLP]
    KI, 1998, v:12, n:1, pp:37- [Journal]
  65. Armin B. Cremers, Joachim M. Buhmann, Sebastian Thrun
    Komplexe lernende Systeme: der mobile Roboter RHINO. [Citation Graph (0, 0)][DBLP]
    KI, 1995, v:9, n:2, pp:48-49 [Journal]
  66. Joachim M. Buhmann, Tilman Lange, Ulrich Ramacher
    Image Segmentation by Networks of Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:5, pp:1010-1031 [Journal]
  67. Tilman Lange, Volker Roth, Mikio L. Braun, Joachim M. Buhmann
    Stability-Based Validation of Clustering Solutions. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:6, pp:1299-1323 [Journal]
  68. Bernd Fischer, Joachim M. Buhmann
    Path-Based Clustering for Grouping of Smooth Curves and Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2003, v:25, n:4, pp:513-518 [Journal]
  69. Bernd Fischer, Joachim M. Buhmann
    Bagging for Path-Based Clustering. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2003, v:25, n:11, pp:1411-1415 [Journal]
  70. Thomas Hofmann, Joachim M. Buhmann
    Pairwise Data Clustering by Deterministic Annealing. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1997, v:19, n:1, pp:1-14 [Journal]
  71. Thomas Hofmann, Joachim M. Buhmann
    Correction to "Pairwise Data Clustering by Deterministic Annealing". [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1997, v:19, n:2, pp:192- [Journal]
  72. Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    Unsupervised Texture Segmentation in a Deterministic Annealing Framework. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1998, v:20, n:8, pp:803-818 [Journal]
  73. Thomas Zöller, Joachim M. Buhmann
    Robust Image Segmentation Using Resampling and Shape Constraints. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2007, v:29, n:7, pp:1147-1164 [Journal]
  74. Hansjörg Klock, Joachim M. Buhmann
    Data visualization by multidimensional scaling: a deterministic annealing approach. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2000, v:33, n:4, pp:651-669 [Journal]
  75. Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann
    A theory of proximity based clustering: structure detection by optimization. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2000, v:33, n:4, pp:617-634 [Journal]
  76. Julian Laub, Volker Roth, Joachim M. Buhmann, Klaus-Robert Müller
    On the information and representation of non-Euclidean pairwise data. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2006, v:39, n:10, pp:1815-1826 [Journal]
  77. Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann
    Histogram clustering for unsupervised segmentation and image retrieval. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1999, v:20, n:9, pp:899-909 [Journal]
  78. Martin Lades, Jan C. Vorbrüggen, Joachim M. Buhmann, Jörg Lange, Christoph von der Malsburg, Rolf P. Würtz, Wolfgang Konen
    Distortion Invariant Object Recognition in the Dynamic Link Architecture. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Computers, 1993, v:42, n:3, pp:300-311 [Journal]
  79. Lothar Hermes, Joachim M. Buhmann
    A minimum entropy approach to adaptive image polygonization. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Image Processing, 2003, v:12, n:10, pp:1243-1258 [Journal]
  80. Jan Puzicha, Marcus Held, Jens Ketterer, Joachim M. Buhmann, Dieter W. Fellner
    On spatial quantization of color images. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Image Processing, 2000, v:9, n:4, pp:666-682 [Journal]
  81. Joachim M. Buhmann, Hans Kühnel
    Vector quantization with complexity costs. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1993, v:39, n:4, pp:1133-1145 [Journal]
  82. Björn Ommer, Joachim M. Buhmann
    Learning the Compositional Nature of Visual Objects. [Citation Graph (0, 0)][DBLP]
    CVPR, 2007, pp:- [Conf]
  83. Tilman Lange, Joachim M. Buhmann
    Regularized Data Fusion Improves Image Segmentation. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2007, pp:234-243 [Conf]
  84. Tilman Lange, Joachim M. Buhmann
    Kernel-Based Grouping of Histogram Data. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:632-639 [Conf]
  85. Björn Ommer, Joachim M. Buhmann
    Compositional Object Recognition, Segmentation, and Tracking in Video. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2007, pp:318-333 [Conf]
  86. Peter Orbanz, Samuel Braendle, Joachim M. Buhmann
    Bayesian Order-Adaptive Clustering for Video Segmentation. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2007, pp:334-349 [Conf]
  87. Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann
    Cluster analysis of heterogeneous rank data. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:113-120 [Conf]
  88. Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller
    Denoising and Dimension Reduction in Feature Space. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:185-192 [Conf]
  89. Bernd Fischer, Volker Roth, Joachim M. Buhmann
    Time-Series Alignment by Non-negative Multiple Generalized Canonical Correlation Analysis. [Citation Graph (0, 0)][DBLP]
    WILF, 2007, pp:505-511 [Conf]

  90. A class of probabilistic models for role engineering. [Citation Graph (, )][DBLP]


  91. A probabilistic approach to hybrid role mining. [Citation Graph (, )][DBLP]


  92. Probabilistic image registration and anomaly detection by nonlinear warping. [Citation Graph (, )][DBLP]


  93. Automatic Detection of Learnability under Unreliable and Sparse User Feedback. [Citation Graph (, )][DBLP]


  94. Weakly Supervised Cell Nuclei Detection and Segmentation on Tissue Microarrays of Renal Clear Cell Carcinoma. [Citation Graph (, )][DBLP]


  95. Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma. [Citation Graph (, )][DBLP]


  96. Expectation-maximization for sparse and non-negative PCA. [Citation Graph (, )][DBLP]


  97. Optimized expected information gain for nonlinear dynamical systems. [Citation Graph (, )][DBLP]


  98. Multi-assignment clustering for Boolean data. [Citation Graph (, )][DBLP]


  99. PerformancePrediction Challenge. [Citation Graph (, )][DBLP]


  100. Kernel Expansion for Online Preference Tracking. [Citation Graph (, )][DBLP]


  101. Randomized Tree Ensembles for Object Detection in Computational Pathology. [Citation Graph (, )][DBLP]


  102. Computational Pathology Analysis of Tissue Microarrays Predicts Survival of Renal Clear Cell Carcinoma Patients. [Citation Graph (, )][DBLP]


  103. Graph-Based Pancreatic Islet Segmentation for Early Type 2 Diabetes Mellitus on Histopathological Tissue. [Citation Graph (, )][DBLP]


  104. Geometrical Consistent 3D Tracing of Neuronal Processes in ssTEM Data. [Citation Graph (, )][DBLP]


  105. Classification of Multi-labeled Data: A Generative Approach. [Citation Graph (, )][DBLP]


  106. Entropy and Margin Maximization for Structured Output Learning. [Citation Graph (, )][DBLP]


  107. Complex Statistical Models for Object Recognition and Mass Spectrometry. [Citation Graph (, )][DBLP]


  108. Proteome Coverage Prediction for Integrated Proteomics Datasets. [Citation Graph (, )][DBLP]


  109. On the definition of role mining. [Citation Graph (, )][DBLP]


  110. Stable Bayesian Parameter Estimation for Biological Dynamical Systems. [Citation Graph (, )][DBLP]


  111. Music preference learning with partial information. [Citation Graph (, )][DBLP]


  112. Manifold regularization for semi-supervised sequential learning. [Citation Graph (, )][DBLP]


  113. Adaptive bandwidth selection for biomarker discovery in mass spectrometry. [Citation Graph (, )][DBLP]


  114. Sensory segmentation with coupled neural oscillators. [Citation Graph (, )][DBLP]


  115. PepSplice: cache-efficient search algorithms for comprehensive identification of tandem mass spectra. [Citation Graph (, )][DBLP]


  116. Proteome coverage prediction with infinite Markov models. [Citation Graph (, )][DBLP]


  117. Time-series alignment by non-negative multiple generalized canonical correlation analysis. [Citation Graph (, )][DBLP]


  118. Information theoretic model validation for clustering [Citation Graph (, )][DBLP]


Search in 0.006secs, Finished in 0.462secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002