10.1162/153244303322753616

From MaRDI portal
Publication:4827807

DOI10.1162/153244303322753616zbMath1102.68556OpenAlexW2119479037MaRDI QIDQ4827807

André Elisseeff, Isabelle Guyon

Publication date: 23 November 2004

Published in: CrossRef Listing of Deleted DOIs (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/153244303322753616



Related Items

Forward selection method with regression analysis for optimal gene selection in cancer classification, Unnamed Item, On the combination of kernel principal component analysis and neural networks for process indirect control, Crop prediction based on soil and environmental characteristics using feature selection techniques, Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models, Interactive evolutionary approaches to multiobjective feature selection, Similarity interaction in information-theoretic self-organizing maps, Combining clustering of variables and feature selection using random forests, Variable selection in classification model via quadratic programming, Objective Selection for Cancer Treatment: An Inverse Optimization Approach, Finite element model updating using Hamiltonian Monte Carlo techniques, Unsupervised feature selection via adaptive autoencoder with redundancy control, Sparse optimization via vector \(k\)-norm and DC programming with an application to feature selection for support vector machines, Statistical Inference, Learning and Models in Big Data, Data poisoning against information-theoretic feature selection, Ellipsoidal buffered area under the curve maximization model with variable selection in credit risk estimation, Cost-constrained group feature selection using information theory, A neurodynamic optimization approach to supervised feature selection via fractional programming, A General Framework of Nonparametric Feature Selection in High-Dimensional Data, A fuzzy set based approach for effective feature selection, Feature selection in machine learning via variable neighborhood search, A novel wrapper-based feature subset selection method using modified binary differential evolution algorithm, Consistent and unbiased variable selection under indepedent features using random forest permutation importance, Algorithm selection on a meta level, How to describe the spatial near-far relations among concepts?, Unnamed Item, Three-way weighted combination-entropies based on three-layer granular structures, Optimization of sparsity-constrained neural networks as a mixed integer linear program, Orthogonally constrained matrix factorization for robust unsupervised feature selection with local preserving, Separability, contextuality, and the quantum frame problem, Optimization of team selection in fantasy cricket: a hybrid approach using recursive feature elimination and genetic algorithm, Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents, Improved feature selection with simulation optimization, Multi-dimensional Bayesian network classifiers for partial label ranking, Post-selection inference via algorithmic stability, An integrated surrogate model constructing method: annealing combinable Gaussian process, A Large-Scale Optimization Method Using a Sparse Approximation of the Hessian for Magnetic Resonance Fingerprinting, Robust Data-Driven Fault Detection in Dynamic Process Environments Using Discrete Event Systems, Unnamed Item, LEARNING GRADIENTS FROM NONIDENTICAL DATA, Unnamed Item, Analyzing non-stationarity in cement stone pit by median polish interpolation: a case study, The Support Feature Machine: Classification with the Least Number of Features and Application to Neuroimaging Data, Independent screening in high-dimensional exponential family predictors’ space, Performance-weighted ensembles of random forests for predicting price impact, Scalable Semisupervised Functional Neurocartography Reveals Canonical Neurons in Behavioral Networks, Neural Decoding with Kernel-Based Metric Learning, Distance-based variable generation with applications to the FACT experiment, Stochastic correlation coefficient ensembles for variable selection, The extended Granger causality analysis for Hodgkin–Huxley neuronal models, Convex Optimization for Group Feature Selection in Networked Data, Decomposition rules for quantum Rényi mutual information with an application to information exclusion relations, Minimization of Akaike's information criterion in linear regression analysis via mixed integer nonlinear program, Combined SVM-based feature selection and classification, A New Hybrid Binary Algorithm of Bat Algorithm and Differential Evolution for Feature Selection and Classification, Unnamed Item, Efficient least angle regression for identification of linear-in-the-parameters models, Including network knowledge into Cox regression models for biomarker signature discovery, Input Variable Selection in Neural Network Models, Unnamed Item, Combined SVM-based feature selection and classification, Why CP Portfolio Solvers Are (under)Utilized? Issues and Challenges, Multi‐objective feature selection using a Bayesian artificial immune system, High-Dimensional Discriminant Analysis, Forward-Backward Selection with Early Dropping, A quarterly time-series classifier based on a reduced-dimension generated rules method for identifying financial distress, Functional Network Topology Learning and Sensitivity Analysis Based on ANOVA Decomposition, Feature Selection via Coalitional Game Theory, Variable Selection for Nonparametric Learning with Power Series Kernels, Controlling the False Discovery Rate for Feature Selection in High‐resolution NMR Spectra, A novel support vector classifier for longitudinal high‐dimensional data and its application to neuroimaging data, A variance reduction framework for stable feature selection, Support Vector Machines for Dyadic Data, Unnamed Item, Feature selection for cross-scene hyperspectral image classification using cross-domain ReliefF, Unnamed Item, Fuzzy Entropy Used for Predictive Analytics, Unnamed Item, An ensemble ofk-nearest neighbours algorithm for detection of Parkinson's disease, Benchmark and Survey of Automated Machine Learning Frameworks, Unnamed Item, Manifold Based Data Refinement for Biological Analysis, A Novel Approach to Feature Selection Based on Quality Estimation Metrics, Interpretable Approximation of High-Dimensional Data, Sobol Sensitivity: A Strategy for Feature Selection, A Detailed Study of the Distributed Rough Set Based Locality Sensitive Hashing Feature Selection Technique, The independent component analysis with the linear regression – predicting the energy costs of the public sector buildings in Croatia, Morphological Texture Description from Multispectral Skin Images in Cosmetology, High-Dimensional Data Classification, Sparse high-dimensional fractional-norm support vector machine via DC programming, On selecting interacting features from high-dimensional data, Estimating mutual information for feature selection in the presence of label noise, Physically interpretable machine learning algorithm on multidimensional non-linear fields, Variable selection by random forests using data with missing values, Nonparametric feature selection by random forests and deep neural networks, Rank-based classifiers for extremely high-dimensional gene expression data, Ensemble feature selection for high dimensional data: a new method and a comparative study, Clustering, multicollinearity, and singular vectors, The randomized information coefficient: assessing dependencies in noisy data, An opinion formation based binary optimization approach for feature selection, Local rough set: a solution to rough data analysis in big data, Lagrangian relaxation for SVM feature selection, Logitboost autoregressive networks, Joint feature selection and classification for positive unlabelled multi-label data using weighted penalized empirical risk minimization, The backbone method for ultra-high dimensional sparse machine learning, Inadequacy of linear methods for minimal sensor placement and feature selection in nonlinear systems: a new approach using secants, Chunking and cooperation in particle swarm optimization for feature selection, Grouped variable importance with random forests and application to multiple functional data analysis, Probing for sparse and fast variable selection with model-based boosting, A unified definition of mutual information with applications in machine learning, Evolutionary feature selection for big data classification: a MapReduce approach, Budget constrained non-monotonic feature selection, Finding the best not the most: regularized loss minimization subgraph selection for graph classification, A survey of outlier detection in high dimensional data streams, Training trees on tails with applications to portfolio choice, On the relation between the true and sample correlations under Bayesian modelling of gene expression datasets, Unsupervised feature selection by regularized self-representation, Generation of rough sets reducts and constructs based on inter-class and intra-class information, Set characterization-selection towards classification based on interaction index, A center sliding Bayesian binary classifier adopting orthogonal polynomials, Synergies between operations research and data mining: the emerging use of multi-objective approaches, Non parametric statistical models for on-line text classification, Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques, High dimensional data classification and feature selection using support vector machines, A fast heuristic attribute reduction approach to ordered decision systems, Analyzing high dimensional correlated data using feature ranking and classifiers, A mixed integer programming-based global optimization framework for analyzing gene expression data, Rescorla-Wagner models with sparse dynamic attention, Swamping and masking in Markov boundary discovery, Lossy compression approach to subspace clustering, Variable selection for binary classification in large dimensions: comparisons and application to microarray data, \(k\)-maxitive fuzzy measures: a scalable approach to model interactions, Score-based methods for learning Markov boundaries by searching in constrained spaces, Sequential approaches for learning datum-wise sparse representations, Convolutional neural network learning for generic data classification, A new multi-colony fairness algorithm for feature selection, Heuristic-based feature selection for rough set approach, How to choose biomarkers in view of parameter estimation, Semi-supervised local Fisher discriminant analysis for dimensionality reduction, Composite kernel learning, Bayesian instance selection for the nearest neighbor rule, A semi-parallel framework for greedy information-theoretic feature selection, Regularized greedy column subset selection, Residual selection for fault detection and isolation using convex optimization, A hybrid DE-RGSO-ELM for brain tumor tissue categorization in 3D magnetic resonance images, Multi-label feature ranking with ensemble methods, Unsupervised dimensionality reduction versus supervised regularization for classification from sparse data, An adaptive heuristic for feature selection based on complementarity, A new method for solving supervised data classification problems, An instance voting approach to feature selection, Cost-sensitive feature selection for support vector machines, Robust \(L_p\)-norm least squares support vector regression with feature selection, Variable selection of high-dimensional non-parametric nonlinear systems by derivative averaging to avoid the curse of dimensionality, Ranking the importance of variables in nonlinear system identification, Feature selection based on fuzzy joint mutual information maximization, Rough set-based feature selection for weakly labeled data, Hyperparameter optimization in learning systems, An efficient binary gradient-based optimizer for feature selection, Integer matrix approximation and data mining, A multi-objective evolutionary algorithm for feature selection based on mutual information with a new redundancy measure, Variable selection methods for model-based clustering, Membership-margin based feature selection for mixed type and high-dimensional data: theory and applications, Towards scalable fuzzy-rough feature selection, Adaptive graph construction using data self-representativeness for pattern classification, A decision analytic approach to predicting quality of life for lung transplant recipients: a hybrid genetic algorithms-based methodology, An optimization approach to epistasis detection, Metaheuristics for data mining, Measuring instance difficulty for combinatorial optimization problems, Benchmark for filter methods for feature selection in high-dimensional classification data, Using machine learning to improve cylindrical algebraic decomposition, Survival prediction and feature selection in patients with breast cancer using support vector regression, Chained correlations for feature selection, Bounded-abstaining classification for breast tumors in imbalanced ultrasound images, Machine-learning-based modeling of coarse-scale error, with application to uncertainty quantification, Hybridizing principles of the Electre method with case-based reasoning for data mining: Electre-CBR-I and Electre-CBR-II, Feature selection with dynamic mutual information, Reference-point-based multi-objective optimization algorithm with opposition-based voting scheme for multi-label feature selection, Parsimonious additive models, High-dimensional data clustering, A simple and efficient method for variable ranking according to their usefulness for learning, Stepwise feature selection using generalized logistic loss, Feature selection using fuzzy support vector machines, Can earnings management information improve bankruptcy prediction models?, A reference model for customer-centric data mining with support vector machines, TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions, A neural network based multi-class trading strategy for the S\&P 500 index, Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA), Multi-granularity sequential three-way recommendation based on collaborative deep learning, A weighted wrapper approach to feature selection, A novel divide-and-merge classification for high dimensional datasets, A new variable selection approach using random forests, A General Framework for Dimensionality-Reducing Data Visualization Mapping, Information-theoretic approaches to SVM feature selection for metagenome read classification, Information enhancement for interpreting competitive learning, Fuzzy Clustering-Based Filter, Non-parametric classifier-independent feature selection, The Bhattacharyya space for feature selection and its application to texture segmentation, A penalized criterion for variable selection in classification, Advanced conjoint analysis using feature selection via support vector machines, Primal explicit max margin feature selection for nonlinear support vector machines, Simultaneous feature selection and Gaussian mixture model estimation for supervised classification problems, Mixed integer quadratic optimization formulations for eliminating multicollinearity based on variance inflation factor, Robust Naive Bayes Combination of Multiple Classifications, Cluster Data Streams with Noisy Variables, Variable Selection for Clustering with Gaussian Mixture Models, A Bayesian approach to sparse dynamic network identification, A model-free variable selection method for reducing the number of redundant variables, A hybrid feature selection scheme for mixed attributes data, Feature selection based on meta-heuristics for biomedicine, Unnamed Item, Embedded variable selection method using signomial classification, Steganalysis of meshes based on 3D wavelet multiresolution analysis, Selection of time instants and intervals with support vector regression for multivariate functional data, Incremental feature selection based on fuzzy rough sets, Feature weighting as a tool for unsupervised feature selection, Privacy preserving feature selection and multiclass classification for horizontally distributed data, Feature selection using stochastic approximation with Barzilai and Borwein non-monotone gains, Constructing a linear QSAR for some metabolizable drugs by human or pig flavin-containing monooxygenases using some molecular features selected by a genetic algorithm trained SVM, Bayesian optimization with partially specified queries, Unobserved classes and extra variables in high-dimensional discriminant analysis, Can high-order dependencies improve mutual information based feature selection?, Overfitting in linear feature extraction for classification of high-dimensional image data, Global and local structure preserving sparse subspace learning: an iterative approach to unsupervised feature selection, Feature extraction through local learning, Incremental relevance sample-feature machine: a fast marginal likelihood maximization approach for joint feature selection and classification, Hadoop neural network for parallel and distributed feature selection, Integrating data augmentation and hybrid feature selection for small sample credit risk assessment with high dimensionality, A Method for Reducing the Number of Support Vectors in Fuzzy Support Vector Machine, Passenger Profiling and Screening for Aviation Security in the Presence of Strategic Attackers, Why significant variables aren’t automatically good predictors, Two-stage feature selection for classification of gene expression data based on an improved salp swarm algorithm, A machine learning system to improve the performance of ASP solving based on encoding selection, Learning and estimation applications of an online homotopy algorithm for a generalization of the LASSO, From Supervised Instance and Feature Selection Algorithms to Dual Selection: A Review, Sparse Matrix Feature Selection in Multi-label Learning, Dominance-Based Neighborhood Rough Sets and Its Attribute Reduction, Stability of the replica symmetric solution in diluted perceptron learning, A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search, Crossclus: user-guided multi-relational clustering, A data-driven forecasting approach for newly launched seasonal products by leveraging machine-learning approaches, Solving a class of feature selection problems via fractional 0--1 programming, Linear feature extraction by integrating pairwise and global discriminatory information via sequential forward floating selection and kernel QR factorization with column pivoting, Qini-based uplift regression, Sparse optimization in feature selection: application in neuroimaging, Invariant optimal feature selection: A distance discriminant and feature ranking based solution, Constraint score: A new filter method for feature selection with pairwise constraints, Multi-group support vector machines with measurement costs: A biobjective approach, On the discovery of events in EEG data utilizing information fusion, Measuring and visualizing the stability of biomarker selection techniques, EdgeMarker: identifying differentially correlated molecule pairs as edge-biomarkers, Unsupervised feature selection with ensemble learning, Feature selection based on loss-margin of nearest neighbor classification, Using pre \& post-processing methods to improve binding site predictions, Feature selection for high-dimensional data, Unnamed Item, An efficient accelerator for attribute reduction from incomplete data in rough set framework, Correntropy based feature selection using binary projection, Supervised classification with conditional Gaussian networks: increasing the structure complexity from naive Bayes, Learning in compressed space, A hybrid and exploratory approach to knowledge discovery in metabolomic data, An efficient semi-supervised representatives feature selection algorithm based on information theory, A survey on semi-supervised feature selection methods, Optimal discretization and selection of features by association rates of joint distributions, On orthogonal feature extraction model with applications in medical prognosis, On Combining Wavelets Expansion and Sparse Linear Models for Regression on Metabolomic Data and Biomarker Selection, Gene selection for cancer classification, Feature selection in SVM via polyhedral \(k\)-norm, Discernibility matrix based incremental feature selection on fused decision tables, Mixed Integer Nonlinear Program for Minimization of Akaike’s Information Criterion, Guided Projections for Analyzing the Structure of High-Dimensional Data, Ensemble Neural Network Approach for Accurate Load Forecasting in a Power System, A screening-based gradient-enhanced Kriging modeling method for high-dimensional problems, Sparse multi-criteria optimization classifier for credit risk evaluation, Sparse kernel deep stacking networks, Information Enhancement Learning: Local Enhanced Information to Detect the Importance of Input Variables in Competitive Learning, Variable Selection for Support Vector Machines, Efficient feature selection using shrinkage estimators, Machine learning approach for locating phase interfaces using conductivity probes, Constrained information maximization by free energy minimization, Investigating consumers' store-choice behavior via hierarchical variable selection, A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification, DNA combinatorial messages and epigenomics: the case of chromatin organization and nucleosome occupancy in eukaryotic genomes, Identification of potential biomarkers on microarray data using distributed gene selection approach, Feature importance ranking for classification in mixed online environments, A distributed feature selection scheme with partial information sharing, Correlation-based ensemble feature selection using bioinspired algorithms and classification using backpropagation neural network, Comprehensibility maximization and humanly comprehensible representations, Learning sparse classifiers with difference of convex functions algorithms, Machine learning for first-order theorem proving, Towards an optimal support vector machine classifier using a parallel particle swarm optimization strategy, Classification and prediction of erythemato-squamous diseases through tensor-based learning, Mathematical optimization in classification and regression trees, MaLeS: a framework for automatic tuning of automated theorem provers, Feature subset selection for logistic regression via mixed integer optimization, Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches, Feature selection via Boolean independent component analysis, An incremental attribute reduction approach based on knowledge granularity under the attribute generalization, A neuro-fuzzy classification technique using dynamic clustering and GSS rule generation, Reducing false positives of network anomaly detection by local adaptive multivariate smoothing, Feature selection filter for classification of power system operating states, Using reinforcement learning to find an optimal set of features, Feature selection for support vector machines using generalized Benders decomposition, Mixed integer second-order cone programming formulations for variable selection in linear regression, Group-wise semiparametric modeling: a SCSE approach, Integer programming models for feature selection: new extensions and a randomized solution algorithm, Selecting features in microarray classification using roc curves, Data mining methods for prediction of air pollution, A survey on feature weighting based K-means algorithms, Towards objective measures of algorithm performance across instance space, Supervised classification and mathematical optimization, Terminated Ramp--Support Vector machines: A nonparametric data dependent kernel, A hybrid differential evolution approach based on surrogate modelling for scheduling bottleneck stages, Support vector machines and neural networks used to evaluate paper manufactured using \textit{Eucalyptus globulus}, Mining non-redundant diverse patterns: an information theoretic perspective, An efficient \(k\) nearest neighbor search for multivariate time series, A trainable feature extractor for handwritten digit recognition, Massively parallel feature selection: an approach based on variance preservation, Sparse non Gaussian component analysis by semidefinite programming, A robust rerank approach for feature selection and its application to pooling-based GWA studies, Multi-model classification method in heterogeneous image databases, A test of independence based on a generalized correlation function, Framing reinforcement learning from human reward: reward positivity, temporal discounting, episodicity, and performance, Exploring the role of graph spectra in graph coloring algorithm performance, Efficient feature selection based on correlation measure between continuous and discrete features, On-line incremental feature weighting in evolving fuzzy classifiers, Feature assembly method for extracting relations in Chinese, A comparison between fixed-basis and variable-basis schemes for function approximation and functional optimization, Classifier variability: accounting for training and testing, Joint Laplacian feature weights learning, Online streaming feature selection using rough sets, Exploiting hidden structure in selecting dimensions that distinguish vectors, Domains of competence of the semi-naive Bayesian network classifiers, Parameterized attribute reduction with Gaussian kernel based fuzzy rough sets, Variable selection in model-based discriminant analysis, An exact approach to sparse principal component analysis, Application of global optimization methods to model and feature selection, Learning sparse gradients for variable selection and dimension reduction, Is mutual information adequate for feature selection in regression?, A hybrid feature selection method based on rough conditional mutual information and naive Bayesian classifier, An information theoretic approach for improving data driven prediction of protein model quality, A multilevel tabu search algorithm for the feature selection problem in biomedical data, Increasing and decreasing returns and losses in mutual information feature subset selection, A greedy feature selection algorithm for big data of high dimensionality, Feature selection using localized generalization error for supervised classification problems using RBFNN, Parallel attribute reduction algorithms using MapReduce, Supersparse linear integer models for optimized medical scoring systems, Accelerating a Gibbs sampler for variable selection on genomics data with summarization and variable pre-selection combining an array DBMS and R, DCA based algorithms for feature selection in multi-class support vector machine, Human activity recognition in AAL environments using random projections, Bidirectional heuristic attribute reduction based on conflict region, Correlation and variable importance in random forests, A generalized eigenvalues classifier with embedded feature selection, Optimization with uniform size queries, Analyzing facial expressions with fuzzy quantification theory. II: Indefinite generalized eigenvalue problem, Supervised feature selection by clustering using conditional mutual information-based distances, IFS-CoCo: instance and feature selection based on cooperative coevolution with nearest neighbor rule, Bagging constraint score for feature selection with pairwise constraints, Discovering influential variables: a method of partitions, A discrete particle swarm optimization method for feature selection in binary classification problems, Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications, Concave programming for minimizing the zero-norm over polyhedral sets, Testing conditional independence in supervised learning algorithms, Feature selection for Bayesian network classifiers using the MDL-FS score, Positive approximation: an accelerator for attribute reduction in rough set theory, SVM-FuzCoC: A novel SVM-based feature selection method using a fuzzy complementary criterion, Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation, Feature subset selection in large dimensionality domains, Optimum simultaneous discretization with data grid models in supervised classification: a Bayesian model selection approach, A new feature selection method for Gaussian mixture clustering, Nominated texture based cervical cancer classification, A centroid-based gene selection method for microarray data classification, Learning heuristics for basic block instruction scheduling, Feature selection via sensitivity analysis of SVM probabilistic outputs, Exploring the boundary region of tolerance rough sets for feature selection, Machine learning with squared-loss mutual information, Variable selection in kernel Fisher discriminant analysis by means of recursive feature elimina\-tion, Efficient computer experiment-based optimization through variable selection, Machine learning feature selection methods for landslide susceptibility mapping, Direct conditional probability density estimation with sparse feature selection, Data mining methods for gene selection on the basis of gene expression arrays, Feature selection for multivariate contribution analysis in fault detection and isolation, Bayesian mixture modeling for multivariate conditional distributions, Core clustering as a tool for tackling noise in cluster labels, An ensemble feature ranking algorithm for clustering analysis, Sparse regression with output correlation for cardiac ejection fraction estimation, Double regularization methods for robust feature selection and SVM classification via DC programming, Sparse hierarchical regression with polynomials, Feature ranking for multi-target regression, Parsimonious classification via generalized linear mixed models