Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Machine Learning
Alignment of trees: an alternative to tree edit
Theoretical Computer Science
Machine Learning
Machine Learning
Discriminant Adaptive Nearest Neighbor Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Logical analysis of numerical data
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems
Theoretical Computer Science
Making large-scale support vector machine learning practical
Advances in kernel methods
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
The String-to-String Correction Problem
Journal of the ACM (JACM)
Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Support vector domain description
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
The cost-minimizing inverse classification problem: a genetic algorithm approach
Decision Support Systems
Enlarging the Margins in Perceptron Decision Trees
Machine Learning
Robust separation of finite sets via quadratics
Computers and Operations Research
Support vector machines: hype or hallelujah?
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
SSVM: A Smooth Support Vector Machine for Classification
Computational Optimization and Applications
Business applications of data mining
Communications of the ACM - Evolving data mining into solutions for insights
Emerging scientific applications in data mining
Communications of the ACM - Evolving data mining into solutions for insights
Support vector machines with different norms: motivation, formulations and results
Pattern Recognition Letters
Machine Learning
Data Mining and Knowledge Discovery
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Support Vector Machines and the Bayes Rule in Classification
Data Mining and Knowledge Discovery
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
Linear Programming Boosting via Column Generation
Machine Learning
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Convergence of a Generalized SMO Algorithm for SVM Classifier Design
Machine Learning
Training Invariant Support Vector Machines
Machine Learning
Interior-Point Methods for Massive Support Vector Machines
SIAM Journal on Optimization
Feature Selection Via Mathematical Programming
INFORMS Journal on Computing
Mathematical Programming for Data Mining: Formulations and Challenges
INFORMS Journal on Computing
A MINSAT Approach for Learning in Logic Domains
INFORMS Journal on Computing
Neural Computation
Optimization methods in massive data sets
Handbook of massive data sets
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
A General Framework for Object Detection
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
Efficient svm training using low-rank kernel representations
The Journal of Machine Learning Research
An introduction to variable and feature selection
The Journal of Machine Learning Research
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Benchmarking Least Squares Support Vector Machine Classifiers
Machine Learning
A Feature Selection Newton Method for Support Vector Machine Classification
Computational Optimization and Applications
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
A tutorial on support vector regression
Statistics and Computing
Data mining in metric space: an empirical analysis of supervised learning performance criteria
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Multiple kernel learning, conic duality, and the SMO algorithm
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Knowledge-Based Linear Programming
SIAM Journal on Optimization
The Entire Regularization Path for the Support Vector Machine
The Journal of Machine Learning Research
Feature Space Interpretation of SVMs with Indefinite Kernels
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multicategory Proximal Support Vector Machine Classifiers
Machine Learning
A survey on tree edit distance and related problems
Theoretical Computer Science
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
The Journal of Machine Learning Research
Protein homology detection using string alignment kernels
Bioinformatics
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
Learning Weighted Metrics to Minimize Nearest-Neighbor Classification Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Market basket analysis in a multiple store environment
Decision Support Systems
Trading convexity for scalability
ICML '06 Proceedings of the 23rd international conference on Machine learning
An Experimental Evaluation of Some Classification Methods
Journal of Global Optimization
Rule-Based Learning Systems for Support Vector Machines
Neural Processing Letters
Computer assisted customer churn management: State-of-the-art and future trends
Computers and Operations Research
Bounds on Error Expectation for Support Vector Machines
Neural Computation
Training a Support Vector Machine in the Primal
Neural Computation
The Interplay of Optimization and Machine Learning Research
The Journal of Machine Learning Research
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
The Journal of Machine Learning Research
Building Support Vector Machines with Reduced Classifier Complexity
The Journal of Machine Learning Research
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
The Journal of Machine Learning Research
Large Scale Multiple Kernel Learning
The Journal of Machine Learning Research
The Journal of Machine Learning Research
An Efficient Implementation of an Active Set Method for SVMs
The Journal of Machine Learning Research
Rule Extraction from Support Vector Machines: A Sequential Covering Approach
IEEE Transactions on Knowledge and Data Engineering
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
Proceedings of the 24th international conference on Machine learning
Support vector machines with adaptive Lq penalty
Computational Statistics & Data Analysis
A convergent decomposition algorithm for support vector machines
Computational Optimization and Applications
Top 10 algorithms in data mining
Knowledge and Information Systems
Multi-group support vector machines with measurement costs: A biobjective approach
Discrete Applied Mathematics
Optimization Techniques for Semi-Supervised Support Vector Machines
The Journal of Machine Learning Research
Robust support vector machines for classification and computational issues
Optimization Methods & Software - Systems Analysis, Optimization and Data Mining in Biomedicine
Dimensionality Reduction for Classification
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Non-smoothness in classification problems
Optimization Methods & Software - THE JOINT EUROPT-OMS CONFERENCE ON OPTIMIZATION, 4-7 JULY, 2007, PRAGUE, CZECH REPUBLIC, PART I
Decompositional Rule Extraction from Support Vector Machines by Active Learning
IEEE Transactions on Knowledge and Data Engineering
Particle swarm optimization for prototype reduction
Neurocomputing
Optimal Expected-Distance Separating Halfspace
Mathematics of Operations Research
Algorithmic Prediction of Health-Care Costs
Operations Research
Novel Optimization Models for Abnormal Brain Activity Classification
Operations Research
Classification and Regression via Integer Optimization
Operations Research
On the Selection of the Globally Optimal Prototype Subset for Nearest-Neighbor Classification
INFORMS Journal on Computing
Quantifying the impact of learning algorithm parameter tuning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A system for induction of oblique decision trees
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Optimal feature selection for support vector machines
Pattern Recognition
Classification by vertical and cutting multi-hyperplane decision tree induction
Decision Support Systems
Kernel based support vector machine via semidefinite programming: Application to medical diagnosis
Computers and Operations Research
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
Binarized Support Vector Machines
INFORMS Journal on Computing
Feature selection combining linear support vector machines and concave optimization
Optimization Methods & Software - DEDICATED TO PROFESSOR VLADIMIR F. DEMYANOV ON THE OCCASION OF HIS 70TH BIRTHDAY
Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training
The Journal of Machine Learning Research
Bundle Methods for Regularized Risk Minimization
The Journal of Machine Learning Research
Machine learning problems from optimization perspective
Journal of Global Optimization
Concave programming for minimizing the zero-norm over polyhedral sets
Computational Optimization and Applications
Optimization Methods & Software - The International Conference on Engineering Optimization (EngOpt 2008)
Learning to classify with missing and corrupted features
Machine Learning
Computational Optimization and Applications
DC models for spherical separation
Journal of Global Optimization
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Pegasos: primal estimated sub-gradient solver for SVM
Mathematical Programming: Series A and B - Special Issue on "Optimization and Machine learning"; Alexandre d’Aspremont • Francis Bach • Inderjit S. Dhillon • Bin Yu
Support Vector Machines with the Ramp Loss and the Hard Margin Loss
Operations Research
Exploiting separability in large-scale linear support vector machine training
Computational Optimization and Applications
Classification through incremental max–min separability
Pattern Analysis & Applications
The Maximum Box Problem for moving points in the plane
Journal of Combinatorial Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
The condensed nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms
IEEE Transactions on Neural Networks
Support vector machine with adaptive parameters in financial time series forecasting
IEEE Transactions on Neural Networks
A nested heuristic for parameter tuning in Support Vector Machines
Computers and Operations Research
| Hi-index | 0.01 |
Data mining techniques often ask for the resolution of optimization problems. Supervised classification, and, in particular, support vector machines, can be seen as a paradigmatic instance. In this paper, some links between mathematical optimization methods and supervised classification are emphasized. It is shown that many different areas of mathematical optimization play a central role in off-the-shelf supervised classification methods. Moreover, mathematical optimization turns out to be extremely useful to address important issues in classification, such as identifying relevant variables, improving the interpretability of classifiers or dealing with vagueness/noise in the data.