Most Accessed Papers in Machine Learning

Source: CiteSeer (11/04/03)

  •   Survey Of Clustering Data Mining Techniques - Berkhin (2002)
  •   A Tutorial on Learning With Bayesian Networks - David Heckerman Heckerma
  •   A Gentle Tutorial of the EM Algorithm and its Application to.. - Bilmes (1998)
  •   Fast Algorithms for Mining Association Rules - Agrawal, Srikant (1994)
  •   A Tutorial on Support Vector Machines for Pattern Recognition - Burges (1998)
  •   Mining Association Rules between Sets of Items in Large Databases - Agrawal, Imielinski, Swami (1993)
  •   Data Clustering: A Review - Jain, Murty (1999)
  •   Indexing by Latent Semantic Analysis - Deerwester, Dumais, Furnas.. (1990)
  •   Genetic Programming - Koza (1997)
  •   An Analysis of Recent Work on Clustering Algorithms - Fasulo (1999)
  •   Web Mining: Information and Pattern Discovery on the World Wide Web - Cooley, Mobasher, Srivastava (1997)
  •   Statistical Pattern Recognition: A Review - Jain, Duin, Mao (1999)
  •   Learning Bayesian Networks: The Combination of Knowledge and.. - Heckerman, Geiger, Chickering (1994)
  •   A re-examination of text categorization methods - Yang, Liu (1999)
  •   A Tutorial on Learning Bayesian Networks - Heckerman (1995)
  •   A Comparative Study on Feature Selection in Text Categorization - Yang, Pedersen (1997)
  •   A Genetic Algorithm Tutorial - Whitley (1993)
  •   Predicting the Stock Market - Hellstr”m, Holmstr”m (1998)
  •   Web Mining Research: A Survey - Kosala, Blockeel (2000)
  •   Probabilistic Principal Component Analysis - Tipping, Bishop (1999)
  •   Support-Vector Networks - Cortes, Vapnik (1995)
  •   A Tutorial on Support Vector Regression - Smola, Sch”lkopf (1998)
  •   Evolving Artificial Neural Networks - Yao (1999)
  •   BIRCH: An Efficient Data Clustering Method for Very Large Databases - Tian Zhang Omputer (1999)
  •   An Evaluation of Statistical Approaches to Text Categorization - Yang (1997)
  •   Text Categorization with Support Vector Machines: Learning with Many.. - Joachims (1998)
  •   Mining Sequential Patterns - Agrawal, Srikant (1995)
  •   Web Document Clustering: A Feasibility Demonstration - Zamir, Etzioni (1998)
  •   Complements to 'Pattern Recognition and Neural Networks' - Ripley (1996)
  •   The Hierarchical Hidden Markov Model: Analysis and Applications - Fine, Singer, Tishby (1998)
  •   Bagging Predictors - Breiman (1996)
  •   The EM Algorithm - Russell (1998)
  •   Mining Generalized Association Rules - Srikant, Agrawal (1995)
  •   CURE: An Efficient Clustering Algorithm for Large Databases - Guha, Rastogi, Shim (1998)
  •   A Comparison of Event Models for Naive Bayes Text Classification - Mccallum, Nigam (1998)
  •   Fast Full-Search Equivalent Nearest-Neighbour Search Algorithms - Chua (1999)
  •   Efficient and Effective Clustering Methods for Spatial Data Mining - Ng, Han (1994)
  •   Noisy Time Series Prediction using a Recurrent Neural Network and.. - Giles, Lawrence, Tsoi (2001)
  •   Genetic Algorithms in Timetabling and Scheduling - Fang (1994)
  •   Reinforcement Learning: A Survey - Kaelbling, Littman, Moore (1996)
  •   Enhancing Learning using Feature and Example Selection - Raman, Ioerger (2003)
  •   A Bayesian Approach to Filtering Junk E-Mail - Sahami, Dumais, Heckerman, Horvitz (1998)
  •   Naive Bayesian Learning - Charles Elkan
  •   Evaluation of Hierarchical Clustering Algorithms for Document Datasets - Zhao, Karypis (2002)
  •   An experimental comparison of several clustering and initialization.. - Melia (1998)
  •   Data Mining Approaches for Intrusion Detection - Lee, Stolfo (1998)
  •   Algorithms for Association Rule Mining - A General Survey and.. - Hipp, Gntzer, Nakhaeizadeh (2000)
  •   Refining Initial Points for K-Means Clustering - Bradley, Fayyad (1998)
  •   SOM PAK: The Self-Organizing Map Program Package - Kohonen, Hynninen, Kangas, Laaksonen (1996)