New Algorithms for Efficient High-Dimensional Nonparametric Classification
暂无分享,去创建一个
[1] J. Hammersley. The Distribution of Distance in a Hypersphere , 1950 .
[2] Peter E. Hart,et al. Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.
[3] C. G. Hilborn,et al. The Condensed Nearest Neighbor Rule , 1967 .
[4] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[5] Chin-Liang Chang,et al. Finding Prototypes For Nearest Neighbor Classifiers , 1974, IEEE Transactions on Computers.
[6] Keinosuke Fukunaga,et al. A Branch and Bound Algorithm for Computing k-Nearest Neighbors , 1975, IEEE Transactions on Computers.
[7] Hugh B. Woodruff,et al. An algorithm for a selective nearest neighbor decision rule (Corresp.) , 1975, IEEE Trans. Inf. Theory.
[8] Jon Louis Bentley,et al. An Algorithm for Finding Best Matches in Logarithmic Expected Time , 1976, TOMS.
[9] Norman R. Draper,et al. Applied regression analysis (2. ed.) , 1981, Wiley series in probability and mathematical statistics.
[10] I. Sethi. A Fast Algorithm for Recognizing Nearest Neighbors , 1981, IEEE Transactions on Systems, Man, and Cybernetics.
[11] L. Devroye,et al. 8 Nearest neighbor methods in discrimination , 1982, Classification, Pattern Recognition and Reduction of Dimensionality.
[12] Michael McGill,et al. Introduction to Modern Information Retrieval , 1983 .
[13] Antonin Guttman,et al. R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.
[14] Franco P. Preparata,et al. Computational Geometry , 1985, Texts and Monographs in Computer Science.
[15] Michael Ian Shamos,et al. Computational geometry: an introduction , 1985 .
[16] Stephen M. Omohundro,et al. Efficient Algorithms with Neural Network Behavior , 1987, Complex Syst..
[17] Stephen M. Omohundro,et al. Bumptrees for Efficient Function, Constraint and Classification Learning , 1990, NIPS.
[18] T. Landauer,et al. Indexing by Latent Semantic Analysis , 1990 .
[19] Jeffrey K. Uhlmann,et al. Satisfying General Proximity/Similarity Queries with Metric Trees , 1991, Inf. Process. Lett..
[20] K. Wakimoto,et al. Efficient and Effective Querying by Image Content , 1994 .
[21] Andrew W. Moore,et al. Multiresolution Instance-Based Learning , 1995, IJCAI.
[22] Douglas W. Oard,et al. A survey of information retrieval and filtering methods , 1995 .
[23] Dragutin Petkovic,et al. Query by Image and Video Content: The QBIC System , 1995, Computer.
[24] Robert Tibshirani,et al. Discriminant Adaptive Nearest Neighbor Classification , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Tian Zhang,et al. BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.
[26] Bernhard Schölkopf,et al. Improving the Accuracy and Speed of Support Vector Machines , 1996, NIPS.
[27] Peter L. Bartlett,et al. The Canonical Distortion Measure in Feature Space and 1-NN Classification , 1997, NIPS.
[28] Kevin W. Bowyer,et al. Combination of Multiple Classifiers Using Local Accuracy Estimates , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[29] Pavel Zezula,et al. M-tree: An Efficient Access Method for Similarity Search in Metric Spaces , 1997, VLDB.
[30] Essaid Bouktache,et al. A Fast Algorithm for the Nearest-Neighbor Classifier , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[31] Claire Cardie,et al. Improving Minority Class Prediction Using Case-Specific Feature Weights , 1997, ICML.
[32] Salvatore J. Stolfo,et al. Credit Card Fraud Detection Using Meta-Learning: Issues and Initial Results 1 , 1997 .
[33] Yoshihiko Hamamoto,et al. A Bootstrap Technique for Nearest Neighbor Classifier Design , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[34] G. Gates. The Reduced Nearest Neighbor Rule , 1998 .
[35] Sunil Arya,et al. An optimal algorithm for approximate nearest neighbor searching fixed dimensions , 1998, JACM.
[36] Soo-Ik Chae,et al. Fast Design of Reduced-Complexity Nearest-Neighbor Classifiers Using Triangular Inequality , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[37] J. C. BurgesChristopher. A Tutorial on Support Vector Machines for Pattern Recognition , 1998 .
[38] Thorsten Joachims,et al. Making large scale SVM learning practical , 1998 .
[39] Arnold W. M. Smeulders,et al. Image Databases and Multi-Media Search , 1998, Image Databases and Multi-Media Search.
[40] Thorsten Joachims,et al. Making large-scale support vector machine learning practical , 1999 .
[41] Robert R. Snapp,et al. The labelled cell classifier: a fast approximation to k nearest neighbors , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).
[42] Andrew W. Moore,et al. Accelerating exact k-means algorithms with geometric reasoning , 1999, KDD '99.
[43] Piotr Indyk,et al. Similarity Search in High Dimensions via Hashing , 1999, VLDB.
[44] John C. Platt,et al. Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .
[45] B. Schölkopf,et al. Advances in kernel methods: support vector learning , 1999 .
[46] Richard F. Gunst,et al. Applied Regression Analysis , 1999, Technometrics.
[47] Andrew W. Moore,et al. The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data , 2000, UAI.
[48] H. Aso,et al. A fast algorithm for a k‐NN classifier based on the branch and bound method and computational quantity estimation , 2000 .
[49] Andrew W. Moore,et al. 'N-Body' Problems in Statistical Learning , 2000, NIPS.
[50] Edwin P. D. Pednault,et al. Handling Imbalanced Data Sets in Insurance Risk Modeling , 2000 .
[51] Alexander Tropsha,et al. Novel Variable Selection Quantitative Structure-Property Relationship Approach Based on the k-Nearest-Neighbor Principle , 2000, J. Chem. Inf. Comput. Sci..
[52] A fast algorithm for a k-NN classifier based on the branch and bound method and computational quantity estimation , 2000, Systems and Computers in Japan.
[53] Piotr Indyk,et al. On Approximate Nearest Neighbors under linfinity Norm , 2001, J. Comput. Syst. Sci..
[54] David M. Mount,et al. The Analysis of a Probabilistic Approach to Nearest Neighbor Searching , 2001, WADS.
[55] Dennis DeCoste,et al. Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry , 2002, ICML.
[56] Gustavo E. A. P. A. Batista,et al. Learning with Skewed Class Distributions , 2002 .
[57] Thomas G. Dietterich,et al. Editors. Advances in Neural Information Processing Systems , 2002 .
[58] K. Clarkson. Nearest Neighbor Searching in Metric Spaces : Experimental Results for sb ( S ) , 2002 .
[59] Dennis DeCoste,et al. Anytime Query-Tuned Kernel Machines via Cholesky Factorization , 2003, SDM.
[60] Andrew W. Moore,et al. Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs , 2003, AISTATS.
[61] Christopher Krügel,et al. Anomaly detection of web-based attacks , 2003, CCS '03.
[62] Dominic Mazzoni,et al. Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors , 2003, ICML.
[63] Yanjun Qi,et al. Supervised classification for video shot segmentation , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).
[64] Alex Pentland,et al. Photobook: Content-based manipulation of image databases , 1996, International Journal of Computer Vision.
[65] Andrew W. Moore,et al. An Investigation of Practical Approximate Nearest Neighbor Algorithms , 2004, NIPS.
[66] Andrew W. Moore,et al. The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data , 2004, KDD.
[67] Steven Salzberg,et al. A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features , 2004, Machine Learning.
[68] Christos Faloutsos,et al. Efficient and effective Querying by Image Content , 1994, Journal of Intelligent Information Systems.
[69] Tom Fawcett,et al. Adaptive Fraud Detection , 1997, Data Mining and Knowledge Discovery.
[70] Sargur N. Srihari,et al. Fast k-nearest neighbor classification using cluster-based trees , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[71] Chih-Jen Lin,et al. A tutorial on?-support vector machines , 2005 .