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The need for appropriate ways to measure the distance or similarity between data is ubiquitous in machine learning, pattern recognition and data mining, but handcrafting such good metrics for specific problems is generally difficult.
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The optimal distance measure for nearest neighbor classification
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Least squares quantization in PCM
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Simple fast algorithms for the editing distance between trees and related problems
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Introduction to Statistical Pattern Recognition
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Amino acid substitution matrices from protein blocks
Steven Henikoff and Jorja G. Henikoff · 1992
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Flexible Metric Nearest Neighbor Classification
Jerome H. Friedman · 1994
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Support-Vector Networks
Corinna Cortes and Vladimir Vapnik · 1995
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A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
Yoav Freund and Robert E. Schapire · 1995
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Efficient Color Histogram Indexing for Quadratic Form Distance Functions
James L. Hafner, Harpreet S. Sawhney, William Equitz, Myron Flickner, and Wayne Niblack · 1995
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Discriminant Adaptive Nearest Neighbor Classification
Trevor Hastie and Robert Tibshirani · 1996
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The Canonical Distortion Measure in Feature Space and 1-NN Classification
Jonathan Baxter and Peter L. Bartlett · 1997
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Multitask Learning
Rich Caruana · 1997
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Luisa Micó and Jose Oncina · 1998
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Learning String-Edit Distance
Eric S. Ristad and Peter N. Yianilos · 1998
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Nonlinear component analysis as a kernel eigenvalue problem
Bernhard Schölkopf, Alexander Smola, and Klaus-Robert Müller · 1998
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Modern Information Retrieval
Ricardo Baeza-Yates and Berthier Ribeiro-Neto · 1999
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The Earth Mover’s Distance as a Metric for Image Retrieval
Yossi Rubner, Carlo Tomasi, and Leonidas J. Guibas · 2000
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A Rank Minimization Heuristic with Application to Minimum Order System Approximation
Maryam Fazel, Haitham Hindi, and Stephen P. Boyd · 2001
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Greedy Function Approximation: A Gradient Boosting Machine
Jerome H. Friedman · 2001
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Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
Peter L. Bartlett and Shahar Mendelson · 2002
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Olivier Bousquet and André Elisseeff · 2002
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A Survey of Dimension Reduction Techniques
Imola K. Fodor · 2002
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Text Classification using String Kernels
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, and Chris Watkins · 2002
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Adjustment Learning and Relevant Component Analysis
Noam Shental, Tomer Hertz, Daphna Weinshall, and Misha Pavel · 2002
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Distance Metric Learning with Application to Clustering with Side-Information
Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart J. Russell · 2002
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Learning Distance Functions using Equivalence Relations
Aharon Bar-Hillel, Tomer Hertz, Noam Shental, and Daphna Weinshall · 2003
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Adaptive Duplicate Detection Using Learnable String Similarity Measures
Mikhail Bilenko and Raymond J. Mooney · 2003
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Learning a Distance Metric from Relative Comparisons
Matthew Schultz and Thorsten Joachims · 2003
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Semi-Supervised Learning on Riemannian Manifolds
Mikhail Belkin and Partha Niyogi · 2004
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Integrating Constraints and Metric Learning in Semi-Supervised Clustering
Mikhail Bilenko, Sugato Basu, and Raymond J. Mooney · 2004
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Convex Optimization
Stephen Boyd and Lieven Vandenberghe · 2004
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Regularized multi-task learning
Theodoros Evgeniou and Massimiliano Pontil · 2004
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Neighbourhood Components Analysis
Jacob Goldberger, Sam Roweis, Geoff Hinton, and Ruslan Salakhutdinov · 2004
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Semi-supervised Learning by Entropy Minimization
Yves Grandvalet and Yoshua Bengio · 2004
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Protein homology detection using string alignment kernels
Hiroto Saigo, Jean-Philippe Vert, Nobuhisa Ueda, and Tatsuya Akutsu · 2004
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Online and batch learning of pseudo-metrics
Shai Shalev-Shwartz, Yoram Singer, and Andrew Y. Ng · 2004
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Learning a Mahalanobis Metric from Equivalence Constraints
Aharon Bar-Hillel, Tomer Hertz, Noam Shental, and Daphna Weinshall · 2005
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A survey on tree edit distance and related problems
Philip Bille · 2005
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Learning a Similarity Metric Discriminatively, with Application to Face Verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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Metric Learning by Collapsing Classes
Amir Globerson and Sam T. Roweis · 2005
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A Bayesian Hierarchical Model for Learning Natural Scene Categories
Fei-Fei Li and Pietro Perona · 2005
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A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance
Andrew McCallum, Kedar Bellare, and Fernando Pereira · 2005
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Smooth minimization of non-smooth functions
Yurii Nesterov · 2005
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Large Margin Methods for Structured and Interdependent Output Variables
Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, and Yasemin Altun · 2005
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Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger, John Blitzer, and Lawrence K. Saul · 2005
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Learning Stochastic Tree Edit Distance
Marc Bernard, Amaury Habrard, and Marc Sebban · 2006
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Online Passive-Aggressive Algorithms
Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, and Yoram Singer · 2006
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A Kernel Method for the Two-Sample-Problem
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and Alexander J. Smola · 2006
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Learning Distance Metrics with Contextual Constraints for Image Retrieval
Steven C. Hoi, Wei Liu, Michael R. Lyu, and Wei-Ying Ma · 2006
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Metric Learning for Text Documents
Guy Lebanon · 2006
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Learning Stochastic Edit Distance: application in handwritten character recognition
Jose Oncina and Marc Sebban · 2006
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Learning Sparse Metrics via Linear Programming
Romer Rosales and Glenn Fung · 2006
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Optimizing amino acid substitution matrices with a local alignment kernel
Hiroto Saigo, Jean-Philippe Vert, and Tatsuya Akutsu · 2006
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Large Margin Component Analysis
Lorenzo Torresani and Kuang-Chih Lee · 2006
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Kernel-based distance metric learning for microarray data classification
Huilin Xiong and Xue-Wen Chen · 2006
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Distance Metric Learning: A Comprehensive Survey
Liu Yang and Rong Jin · 2006
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Extending the relevant component analysis algorithm for metric learning using both positive and negative equivalence constraints
Dit-Yan Yeung and Hong Chang · 2006
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Learning a Distance Metric by Empirical Loss Minimization
Wei Bian and Dacheng Tao · 2011
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Distance Metric Learning under Covariate Shift
Bin Cao, Xiaochuan Ni, Jian-Tao Sun, Gang Wang, and Qiang Yang · 2011
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Ground Metric Learning
Marco Cuturi and David Avis · 2011
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Hierarchical semantic indexing for large scale image retrieval
Jia Deng, Alexander C. Berg, and Li Fei-Fei · 2011
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DAML: Domain Adaptation Metric Learning
Bo Geng, Dacheng Tao, and Chao Xu · 2011
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Multiple Kernel Learning Algorithms
Mehmet Gönen and Ethem Alpaydin · 2011
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Learning Metrics between Tree Structured Data: Application to Image Recognition
Laurent Boyer, Amaury Habrard, and Marc Sebban · 2007
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Information-theoretic metric learning
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, and Inderjit S. Dhillon · 2007
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Matrix Nearness Problems with Bregman Divergences
Inderjit S. Dhillon and Joel A. Tropp · 2007
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Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification
Andrea Frome, Yoram Singer, Fei Sha, and Jitendra Malik · 2007
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An Invariant Large Margin Nearest Neighbour Classifier
M. Pawan Kumar, Philip H. S. Torr, and Andrew Zisserman · 2007
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Automatic learning of cost functions for graph edit distance
Michel Neuhaus and Horst Bunke · 2007
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Learning a mixture of sparse distance metrics for classification and dimensionality reduction
Yi Hong, Quannan Li, Jiayan Jiang, and Zhuowen Tu · 2011
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Generalized sparse metric learning with relative comparisons
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Efficiently Learning a Distance Metric for Large Margin Nearest Neighbor Classification
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Local Distance Functions: A Taxonomy, New Algorithms, and an Evaluation
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High-dimensional covariance estimation by minimizing ℓ 1 \ell_{1} -penalized log-determinant divergence
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Learning a Distance Metric from a Network
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Learning Discriminative Metrics via Generative Models and Kernel Learning
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Metric Learning with Multiple Kernels
Jun Wang, Huyen T. Do, Adam Woznica, and Alexandros Kalousis · 2011
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Multi-Task Low-Rank Metric Learning Based on Common Subspace
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Low Rank Metric Learning with Manifold Regularization
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Supervised Metric Learning with Generalization Guarantees
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Constrained Empirical Risk Minimization Framework for Distance Metric Learning
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Adaptive Regularization for Weight Matrices
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Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning
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A Geometric take on Metric Learning
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Metric and Kernel Learning Using a Linear Transformation
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Metric Learning: A Survey
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