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Links para Reconhecimento de Padrões e Aprendizado de Máquina

Nesta página você vai encontrar uma lista de links para outras páginas contendo informações importantes sobre reconhecimento de padrões. Estes links aqui são links básicos e importantes para seu aprednizado. Sugerimos fortemente que você, no correr do semestre, à medida que os tópicos forem abordados, vá consultando estas páginas para complementar seus conhecimentos.

Links para tutoriais de ferramentas e linguagem de programação você vai encontrar na página de bibliografia deste site.

Esta página está dividida em:

  1. Referências Específicas de Reconhecimento de Padrões
  2. Referências Gerais  de Temas Associados ao Reconhecimento de Padrões
  3. Referências para Aprendizado de Máquina (Machine Learning)
  4. Diretório dos Grupos de Pesquisa em Reconhecimento de Padrões
Observe que alguns dos links podem estar quebrados.  Tentamos manter sempre tudo atualizado, mas nem sempre é possível.

Referências Específicas de Temas de Reconhecimento de Padrões:

1. Introduction to Pattern Recognition via Character Recognition

  1. Notes on Methods of Proof
  2. Introduction to pattern recognition (PostScript)
  3. Digital images
    1. Scan Converting Polygons (Java demo)
    2. Alternatives to pixels
  4. Image processing basics
  5. Optical character recognition (brief introduction)
  6. Handwritten address recognition demonstration
  7. Tessellation Resources
  8. Tessellation Tutorials
  9. Grids:
    1. Grids, connectivity and contour tracing (PostScript)
    2. Contour tracing by radial sweep
    3. Contour Representations
    4. Shapes of unit area in a square unit grid
    5. Contour Tracing Algorithms: Tutorial by Abeer Ghuneim
  10. Digital lines and circles:
    1. A tutorial on the midpoint algorithm
    2. Interactive Java applet of the midpoint algorithm
  11. M.I.T. reading machine for the blind
  12. What is hysteresis?
  13. Zacharia Nkgau's tutorial on hysteresis smoothing of monotonic polygons (with interactive Java applet)
  14. Artistic Image Processing:
    1. Mark Grundland's Fractals from Voronoi Diagrams
  15. Image Segmentation:
    1. Image segmentation tutorial

2. Smoothing, Approximation, Data-Compression and Fitting

  1. Minkowski addition and subtraction (dilation and erosion)
    1. Interactive Java applet
  2. Regularization
  3. Logical smoothing
  4. Local averaging
  5. Median filtering:
    1. Median filtering introduction
    2. Median filtering and salt-and-pepper noise
    3. Adaptive weighted median filtering
  6. Gaussian smoothing
  7. More about Carl Friedrich Gauss
  8. Polygonal Approximation:
    1. Midpoint smoothing
      1. Tutorial and Interactive Java applet by Ziad Hafed and Diana Hernandez
    2. Ramer-Douglas-Peucker algorithm (Iterative End-Points Fit)
      1. Guirlyn Olivar's interactive Java applet
    3. Interactive Java applets by Steve Robbins
    4. Relative Convex Hull Smoothing:
      1. Steve Robbins' Tutorial on Relative Convex Hulls
      2. Relative Convex Hull applet
      3. Computing the Relative Convex Hull and other geodesic properties in a polygon (PostScript)
    5. Graph-theoretic methods:
      1. Applet for Iri-Imai algorithm
    6. Smoothing by Curvature Flow(Java applet)
  9. Smoothing basics (PostScript)
  10. Curve Approximation Java Applet
  11. Line Fitting:
    1. Least-Squares Linear Fit Java Calculator
    2. Data Fitting Between Data Ranges
  12. Smoothing with splines:
    1. Cubic Spline Interactive Java applet
  13. Function Approximation:
    1. Interactive Java applet

3. Differentiation, Sharpening, Enhancement, Caricatures and Shape Morphing

  1. Differentiation and Edge Detection:
    1. Edge detection and the Sobel operator
    2. Canny edge-detector demo
    3. More edge detection
    4. Edge detection tutorial (Wolfram Research)
    5. Roberts cross operator
  2. Enhancement and Lateral Inhibition:
    1. Sharpening, the Laplacian and lateral inhibition in neural networks (PostScript)
    2. Eye and retina
    3. Mach bands and lateral inhibition
    4. The retina and lateral inhibition
    5. The Lateral Inhibition Simulator (interactive Java applet)
    6. Another Lateral Inhibition Java demo
    7. Limulus-the horseshoe crab
  3. The Laplacian:
    1. The Laplacian in edge detection
    2. Laplacian edge detector applet
  4. Caricature Generation:
    1. Ian Garton's tutorial and interactive Java applet
  5. Fundamentals of Visual Perception:
    1. The Joy of Visual Perception
  6. Shape Morphing:
    1. Mark Grundland's morphing bibliography
    2. More morphing references

4. Moment and Fourier Descriptors of Shape

  1. Affine transformations
  2. Affine Geometry
  3. More on affine transformations
  4. Moment Invariants
  5. Moments in Pattern Recognition (PostScript)
    1. Moments of area & perimeter
    2. Moments for feature extraction
    3. Moments for pre-processing
    4. Moments as predictors of discrimination performance
  6. Adam Ramadan's tutorial on moments in pattern recognition
  7. Computing Higher Moments of Polygons (Post Script)
  8. Fourier Descriptors:
    1. Recosntruction of closed curves from Fourier descriptors (Java applet)
    2. Fourier synthesis (Java applet)

5. Skeletons, Distance and Medial Axis Transforms

  1. What is Distance?
    1. Manhattan Metric (Taxicab Geometry)
    2. Pascal Tesson's tutorial on taxicab geometry (with Java applet)
  2. Minkowski metrics
    1. More about Hermann Minkowski
  3. Distance between sets:
    1. Distance between strings
    2. The Maximum Distance
    3. The Minimum Distance
    4. The Hausdorff Distance
    5. Normand Gregoire & Mikael Bouillot's Tutorial on the Hausdorff distance and 

      6. its applications (with interactive Java applet)
    6. The Grenander Distance
  4. Skeletons (PostScript)
    1. Hilditch's algorithm
      1. Danielle Azar's tutorial
    2. Rosenfeld's algorithm
      1. Laleh Tajrobehkar's tutorial
      2. More about Azriel Rosenfeld
    3. Skeletonization software
  5. Medial Axis of Polygonal Sets (prairie-fire transformation)
    1. Morphological Shape Analysis via Medial Axis
    2. Medial Axis tutorial by Hang Fai Lau (with interactive Java applet)
    3. Martin Held's Fire Propagation Algorithm
  6. Distance transforms
  7. Skeleton clean-up via distance transforms
  8. Medial axes via distance transforms
  9. Medial axis transform
  10. Medial axis in 3D with applications
  11. Medial axis software
  12. Medial Axis of Pont Sets (also known as Nearest Point Voronoi Diagrams)
    1. Voronoi diagram applet of points in the plane
    2. Voronoi diagram applet of points on the sphere
  13. Medial Axis in 3D and the Power Crust

6. Shape Decomposition and Topological Features

  1. Polygon Decomposition:
    1. Star-shaped decompositions (compressed PostScript: star.ps.gz)
  2. Convex hulls, concavities and enclosures:
    1. Interactive Java convex hull algorithms in 2D
    2. Clarkson's code for 2D convex hulls

7. Processing Line Drawings

  1. Basics of Chain Coding (PostScript)
    1. Square, circular, and grid-intersect quantization
    2. Probability of obtaining diagonal elements
    3. Geometric Probability
    4. Bertrand's paradox.
    5. More on Bertrand's paradox (with Java applet simulations)
    6. More about Joseph Bertrand
    7. Difference encoding & chain correlation functions
    8. Minkowski metric quantization
  2. Example of character recognition using chain codes

8. Detection of Structure in Noisy Pictures and Dot Patterns

  1. What is a line?
  2. Point-to-curve transformations (Hough transform)
  3. Point-Line duality
    1. Interactive Java Demo
  4. Hough Transforms:
    1. Hough Transform tutorial
    2. Improving the Hough Transform (paper by M. Cohen and G. Toussaint)
      1. Line and circle detection
      2. Hypothesis testing approach
      3. Maximum-entropy quantization
    3. Hough Transform home page (and software)
    4. Hough Transform publications
    5. More Hough Transform code
    6. Interactive histogram with Java applet
  5. GraphTheory:
    1. Graphs
    2. Graph theory terminology
    3. Basic Graph Theory
  6. Proximity graphs:
    1. A Survey of Proximity Graphs
    2. Minimal spanning tree (MST) of a dot pattern
    3. MST interactive Java applet
    4. Delaunay Triangulations and Voronoi diagrams
    5. More about Charles Delaunay
  7. The shape of a set of points:
    1. The relative neighbourhood graph
    2. Sphere-of-influence graphs and applet
    3. Alpha shapes
      1. François Bélair's Tutorial on Alpha Shapes 
      2. Gallery of alpha shapes
      3. Code for computing alpha-shapes (and convex hulls)
    4. Beta skeletons:
      1. Xiaoming Zhong's Tutorial on Beta Skeletons (with interactive Java applet)
    5. Voronoi diagram based methods

9. Simple Classifiers and Neural Networks

  1. Simple Classifiers
    1. Template matching
    2. Minimum-distance classifiers
    3. Metrics
    4. Inner products
    5. Linear discriminant functions
    6. Decision boundaries
  2. Mahalanobis Distance Classifiers
  3. Learning from Examples
  4. Neural Networks:
    1. A Brief Tour of the Brain
    2. Introduction to Neural Networks
    3. Another Introduction to Neural Networks
    4. Dr. Gurney's course on neural networks
      1. Real and artificial neurons
      2. Threshold logic units, perceptrons and simple learning rules
    5. A brief history of Neural Networks
    6. Neural Network Basics (FAQ's)
    7. Formal neurons, linear machines & perceptrons
    8. Separability:
      1. Linear separability
      2. Separating points with circles
    9. Pierre Lang's Neural Network for Character Recognition (with interactive Java applet that recognizes the characters you draw on the screen!)

10. Bayesian decision Theory

  1. Bayesian Decision Theory with Gaussian Distributions - A tutorial by Erin Mcleish
  2. Introductory Statistics Course
  3. Another Introduction to Probability and Statistics
    1. Bayes' Theorem
    2. More about Thomas Bayes
    3. A Bayesian Puzzle
    4. The three-door puzzle (Monty Hall problem)
  4. Basics of Statistical Pattern Recognition (by Richard O. Duda)
  5. More about Richard Duda
  6. Minimum risk classification
  7. Minimum error classification
  8. Discriminant functions (linear, quadratic, polynomial)
    1. Quadric surfaces
    2. Geometry formulas and facts
    3. Discriminant analysis code in MATLAB
  9. The bivariate Gaussian probability density function
  10. Multivariate statistics
  11. Lecture Notes on Statistical Pattern Recognition
  12. Occam's Razor:
    1. Jacob Eliosoff's Tutorial on Occam's Razor in Decision Rules (with JAVA applet)
    2. Occam's Razor
    3. Occam's Razor and Machine Learning
    4. Simplicity, Cross-Validation and Occam's Razor
    5. More about William of Occam

11. Feature Selection: Independence of Measurements, Redundancy, and Synergism

  1. Independent and conditionally independent events
  2. Class-conditional and unconditional independence assumptions in pattern recognition (Tutorial by Simon-Pierre Desrosiers)
  3. Independence, uncorrelation and Gaussian distributions (PostScript notes by Julio Peixoto)
  4. Information theory:
    1. A primer on information theory (PostScipt)
    2. Basic properties of Shannon's entropy and mutual information
    3. Relative entropy and mutual information
    4. From Euclid to entropy (PostScript)
    5. Shannon's equivocation and the Fano bound
    6. More about Claude Shannon
  5. Feature Selection:
    1. Dimensiobality Reduction: Francois Labelle's tutorial (with interactive Java applets)
    2. Simon Plain's tutorial on feature selection (with interactive Java applets)
    3. Feature evaluation criteria:
      1. Kullback-Liebler information
      2. The divergence
      3. The affinity
      4. The Fisher Information
        1. More about Sir Ronald Fisher
        2. Pictures of Fisher
    4. Feature selection methods
    5. A survey of feature selection methods
    6. The best k measurements are not the k best
    7. Models of spatial dependence between features
      1. Space-filling curves (Hilbert and Peano)
      2. Sierpinski curves

12. Non-parametric Learning

  1. General Learning Resources
  2. Perceptrons:
    1. Simple perceptrons and the exclusive OR problem
    2. Applet for Perceptron learning in the exclusive OR problem
  3. Non-parametric training of linear machines
  4. Error-correction procedures
    1. Rosenblatt's Perceptron Learning Algorithm (an interactive Java applet)
  5. The fundamental learning theorem
  6. Multi-layer networks
  7. Competitive Learning:
    1. Applet illustrating many competitive learning algorithms

13. Estimation of Density Functions, Parameters and Classifier Performance

  1. Estimation of Parameters:
    1. Robust estimators of location (Tutorial by Greg Aloupis)
    2. Bias and variance of estimators
  2. Density Estimation:
    1. Kernel density estimation applet
  3. Estimators and Bias (Wolfram Research)
  4. Dimensionality and sample size
  5. Estimation of the probability of misclassification
    1. Resubstitution
    2. Holdout
    3. Data Shuffling
    4. Leave-One-Out
    5. Bootstrap Methods

14. Nearest Neighbor Decision Rules

  1. Nearest Neighbor Decision Rules:
    1. The nearest neighbor rule: a tutorial
    2. The nearest neighbor rule with a reject option
    3. The k-nearest neighbor rule applet
    4. The Cover-Hart bounds
      1. Jensen's inequality
      2. Convexity and Jensen's inequality (proof by induction)
      3. More about Thomas Cover
      4. More about Peter Hart
  2. Efficient search methods for nearest neighbors:
    1. The projection method for searching nearest neighbors
    2. Nearest neighbor searching papers
    3. Approximate nearest neighbor searching
  3. Editing nearest neighbor rules to reduce storage:
    1. Editing training sets with proximity graphs(PostScript)
    2. Sergei Savchenko's tutorial on nearest neighbor editing rules
  4. Nearest neighbor computation software
  5. Bibliography on Nearest Neighbor Methods

15. Using Contextual Information in Pattern Recognition

  1. Using Context in Visual Perception
  2. Infinite Monkey Theorem
  3. Introduction to Markov Processes
  4. More about Andrei Markov
  5. Forward dynamic programming and the Viterbi algorithm
    1. Viterbi algorithm demo for sentence recognition
  6. Combined bottom-up and top-down algorithms

16. Unsupervised Learning & Cluster Analysis

  1. Unsupervised Learning:
    1. Decision-directed learning (the K-means algorithms)
    2. K-Means Interactive Java Applet by Laurent Bonnefille and Nicolas Didier.
  2. Graph-theoretic methods:
    1. Minimal spanning tree methods
    2. Tutorial and Java applet by Mike Soss and Chrislain Razafimahefa
  3. Hierarchical clustering:
    1. Pascal Poupart's tutorial with interactive Java applet
    2. Phylogenetic Trees (A Tutorial)
    3. Clustering software on the Web

17. Support Vector Classifiers

    1. Support Vector Classifiers: A First Look
    2. Tutorial on Support Vector Machines and Vapnik-Chervonenkis (VC) Dimension for Pattern Recognition (PostScript)

      3. Support Vector Applet and References

Referências Genéricas de Pattern Recognition:

  1. Introduction to Pattern Recognition
  2. Pattern Recognition Course on the Web (by Richard O. Duda)
  3. Image Processing Course
  4. Classification Society of North America
  5. Pattern Recognition Information
  6. Pattern Recognition Journals
  7. Machine Learning Resources
  8. Morphing Bibliography of Mark Grundland
  9. Neural Network Information
  10. Neural Network FAQ's
  11. Applets for Neural Networks
  12. Face Recognition Home Page
  13. Handwriting Recognition
  14. Java Demos for Handwriting Recognition
  15. Multivariate Analysis
  16. Iris Data
  17. Software and Hardware for Pattern Recognition Research
  18. Typography
Referências sobre Estatística e Reconhecimento de Padrões:
  1. Elementary Statistics Course
  2. Statistics Glossary
  3. Statistics Java Applets
  4. More Statistics Java Applets
  5. Java Demos for Learning Statistics
  6. Virtual Laboratory in Probability & Satistics (with applets)
  7. Interactive Statistics on the Web
  8. Exploratory Data Analysis
  9. Statistics Glossary
  10. Introductory Statistics Course
  11. Bare Bones of Statistics
  12. Statistics On-line
  13. Statistics Resources
  14. Statistics Teaching Resources
  15. Demos for Learning Statistics
  16. Statistics Virtual Library
  17. Statistics Software
  18. Classification Society
  19. Random Number Generation Tutorial
  20. Luc Devroye's Random Number Generation Links

Visão Computacional e Reconhecimento de Padrões

  1. Computer Vision Bibliography
  2. Computer Vision Links
  3. Computer Vision Home Page
  4. Computer Vision On-Line
  5. Web Resources in Computer Vision
  6. Computer Vision Handbook
  7. Sussex Computer Vision Course
  8. Another on-line Computer Vision Course
  9. Computer Graphics Home Page
  10. Graphics Conference Papers Online
  11. Illusions
  12. Image Processing Algorithms
  13. Image Processing Fundamentals (Delft University Course)
  14. Image Manipulation and Storage
  15. Interactive Imaging Machines
  16. 3D-Vision:

Information Theory:

  1. Information Theory links
  2. Information Theory Home Page
  3. Lectures on Information Theory, Pattern Recognition and Neural Networks
  4. Introduction to Information Theory
  5. Entropy

Computational Linguistics:

  1. Computational Linguistics Page
  2. Survey of Human Language Technology
Links para Aprendizado de Máquina (Machine Learning)

Fonte: This list is maintained by the ML Group at the Austrian Research Institute for Artificial Intelligence (OFAI), 
Vienna, Austria.
It is far from complete and is updated on an irregular basis. 
Please direct comments / suggestions / to Gerhard Widmer(gerhard@ai.univie.ac.at)

Fontes de Informações Gerais sobre ML

  1. David Aha's list of machine learning resources. 
  2. Home pages of (hundreds of) ML researchers (maintained by David W. Aha).
  3. GMD Machine Learning Archive. 
  4. Machine Learning Resources (Paul Nielsen). 
  5. University of California-Irvine (UCI) Machine Learning Page. 
  6. University of Illinois / Urbana (UIUC) AI / ML Page . 
  7. ML Mailing List Archive (moderated by M.Pazzani). 
  8. MLNet - Network of Excellence in Machine Learning (GMD server). 
  9. ILPnet, the Inductive Logic Programming Pan-European Scientific Network.
  10. ILPnet2, Network of Excellence on Inductive Logic Programming (continuation of ILPnet).
  11. Information and links concerning "recursive partitioning" type learning algorithms.
  12. Programme "Learning in Humans and Machines" (European Science Foundation). 
  13. ACL Special Interest Group on Natural Language Learning. 
  14. International Grammatical Inference Community Homepage (Mirror). 
  15. `Programming by Example' Homepage (MIT Media Lab).

Software para Machine Learning e Mineração de Dados (Data Mining)

  1. UC Irvine Repository of ML Programs (FTP). 
  2. C4.5 latest release - patches (Ross Quinlan). 
  3. AutoClass - Information and Source Code. 
  4. MSBN --- The Microsoft Bayesian Networks Modeling Tool. 
  5. MLC++ Machine Learning Library in C++ (R. Kohavi, Stanford Univ.). 
  6. SGI MLC++ 2.0 for / from Silicon Graphics. 
  7. WEKA Machine Learning workbench (Univ. of Waikato, NZ). 
  8. TMiner (Java), by F. Berzal and J. Cubero, University of Granada.
  9. TiMBL 1.0 (Tilburg Memory Based Learner), Tilburg University, The Netherlands. 
  10. LIBSVM (support vector machines library for classification), by C.Chang and C.Lin.
  11. SVM Light (Support Vector Machine), T.Joachims.
  12. SNoW Learning Architecture 2.0 (Univ. of Illinois at Urbana/Champaign).
  13. SUBDUE Substructure Discovery System (University of Texas at Arlington) .
  14. CBA (Classification Based on Associations), National University of Singapore. 
  15. DB2 UDB and Intelligent Miner for educational or research purposes (IBM). 
  16. ROC Convex Hull program for comparing classifiers (T. Fawcett & F. Provost). 
  17. BKD (Bayesian Knowledge Discoverer) -- Induction of Bayesian Belief Networks. 
  18. BAYDA (Bayesian Discriminant Analysis) (Univ. of Helsinki). 
  19. MCLUST / EMCLUST (Model-based Clustering Software). 
  20. MLT - Machine Learning Toolbox (Esprit Project). 
  21. STATLOG (Esprit Project). 
  22. Peter Clark's ML Software (UTexas) . 
  23. Belief Network Power Constructor (Windows NT). 
  24. Imperial College Prolog 1000 Database.

ML Benchmarks e outras fontes de Dados

  1. UC Irvine Machine Learning Repository (HTML, FTP). 
  2. UC Irvine Knowledge Discovery in Databases (KDD) Archive.
  3. DELVE (Data for Evaluating Learning in Valid Experiments) - Univ. of Toronto. 
  4. Proben1 --- A Set of Neural Network Benchmark Problems (Size: ~2Mb !!). 
  5. Proben1 --- Description (Tech Report). 
  6. STATLOG (Esprit Project). 
  7. EconData - Economic Time Series Data (Univ. of Maryland). 
  8. National Space Science Data Center (NSSDC) - Info about many NASA data sets. 
  9. FEDSTATS (links to > 70 statistical agencies in the U.S.). 
  10. United States Census Bureau. 
  11. Extensive US Census Data (Ron Kohavi / SGI): File 1 (12.5 MB), File 2 (10 MB).
  12. RISE -- Repository of Information Sources Used in Information Extraction Tasks (USC/ISI).
  13. KDD-Cup-98 (large dataset + results of competition).

Artigos e Glossários de ML 

  1. ML Papers in PostScript format (UC Berkeley).
  2. Meta-List of Machine Learning Bibliographies (D.Aha/P.Turney).
  3. Bibliography on context-sensitive learning (P.Turney, NRC, Ottawa).
  4. Bibliography on automated text categorisation (F.Sebastiani, Univ. of Pisa).
  5. Information Server of the MLNetII Training Committee (taxonomy + examples of ML concepts).
  6. Glossary of Data Mining Terms (by Two Crows).

Programação em Lógica Indutiva

  1. ILPnet, the Inductive Logic Programming Pan-European Scientific Network.
  2. ILPnet2, Network of Excellence on Inductive Logic Programming (continuation of ILPnet).
  3. ESPRIT Project BRA 6020 (ILP) home page - Kath. Univ. Leuven.
  4. ILP programs (GOLEM,...), datasets, etc. (from Esprit ILP project and ILPNet).
  5. FOIL Sources - latest release (Ross Quinlan). 
  6. Computing Lab, Univ. of Oxford, ILP sources. 
  7. FOCL Macintosh application and user manual.
  8. FOCL Common LISP source code.

Mineração de Dados e Descoberta de Conhecimento

  1. UC Irvine Knowledge Discovery in Databases (KDD) Archive.
  2. Knowledge Discovery Mine, KDD Nuggets, etc. (G. Piatetsky-Shapiro). 
  3. Knowledge Discovery Mine, KDD Nuggets, etc. (NEW - from March 1, 1997). 
  4. The Data Mine (Birmingham). 
  5. KDD Projects Home Pages. 
  6. KDD Page, Vanderbilt University. 
  7. Search engine for quickly searching database research bibliographies.
  8. IJCAI-95 KDD tutorial (U. Fayyad).
  9. Collection of Machine Discovery Terminology.
  10. Data Mining and Knowledge Discovery - an International Journal.
  11. Intelligent Data Analysis (IDA) - An International Journal. 
  12. "Information Shootout Project" - description and data sets.

Agrupamento Conceitual

  1. Mixture Modelling page (D. Dowe).
  2. ECOBWEB: a public domain clustering tool (Y. Reich).

Reinforcement Learning

  1. Reinforcement Learning Archive at GMD.
  2. Reinforcement Learning Repository, Michigan State University.
  3. CMU's Reinforcement Learning Page. 
  4. Rich Sutton's Reinforcement Learning Archive.

Algoritmos Genéticos e Computação Evolutiva

  1. EVONET (European Network of Excellence in Evolutionary Computing). 
  2. The Genetic Algorithms Archive. 

Neural Networks, Pattern Recognition, and Statistics

  1. Learning and Soft Computing (Book + Software, V. Kecman, MIT Press, 2001).
  2. The Backpropagator's Online Reading List and Review. 
  3. Pattern Recognition Page (Delft Univ. of Technology, The Netherlands). 
  4. Kovach Computing Services - Statistics Shareware and useful links. 
  5. GRKPACK software: Fitting Smoothing Spline ANOVA Models for Exponential Families. 
  6. Software for Bayesian learning for neural networks (R. Neal). 
  7. NN Benchmarking Page. 
  8. R - A Public Domain Statistics + Graphics Package

Teoria do Aprendizado Computacional

  1. COLT Home Page.
  2. COLTBIB (extensive bibliography of COLT literature). 
  3. Archive of COLT Conferences.
  4. Archive of ALT Conferences.
  5. Archive of EuroCOLT Conferences.
  6. Archive of AII Workshops.

Empresas

  1. Intelligent Applications, Ltd. (UK; Data Mining). 
  2. KDD Page, IBM Almaden Research Center. 
  3. Silicon Graphics, MLC++ Team. 
  4. Thinkbank, Inc. 
  5. Ultragem Data Mining. 
  6. Knowledge Discovery One, Inc. (KD1). 
  7. RuleQuest Research (J.R.Quinlan). 
  8. PARTEK - Data Analysis and Modelling. 
  9. MIT (Management Intelligenter Technologien) GmbH, Aachen, Germany. 
  10. Megaputer Intelligence. 
  11. MineSoft Ltd. 
  12. SPSS Inc. 
  13. Exclusive Ore Inc. (Data Mining, USA).


Atualizado em Setembro de 2001 (Aldo v. Wangenheim) 

The Cyclops Project
German-Brazilian Cooperation Programme on IT
CNPq GMD DLR