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Publication DateIEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 02/2016, Volume 38, Issue 2, pp. 363 - 375
Discriminative methods (e.g., kernel regression, SVM) have been extensively used to solve problems such as object recognition, image alignment and pose...
Training | intra-sample outliers | Computer vision | errors in variables | Computational modeling | Noise | Estimation | Robust methods | Robustness | Data models | missing data | DISCRIMINANT-ANALYSIS | FACE RECOGNITION | FRAMEWORK | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Robust statistics | Usage | Computer-generated environments | Computer simulation | Analysis
Training | intra-sample outliers | Computer vision | errors in variables | Computational modeling | Noise | Estimation | Robust methods | Robustness | Data models | missing data | DISCRIMINANT-ANALYSIS | FACE RECOGNITION | FRAMEWORK | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Robust statistics | Usage | Computer-generated environments | Computer simulation | Analysis
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Loading Rights1977, Addison-Wesley series in behavioral sciences., ISBN 020104854X, xvii, 588
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Econometrica, ISSN 0012-9682, 11/2014, Volume 82, Issue 6, pp. 2295 - 2326
In the regression-discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In...
Statistical variance | Estimation bias | Musical intervals | Approximation | NOTES AND COMMENTS | Inference | Polynomials | Standard error | Estimators | Point estimators | Confidence interval | alternative asymptotics | robust inference | local polynomials | Regression discontinuity | bias correction | Bias correction | Alternative asymptotics | Robust inference | Local polynomials | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS
Statistical variance | Estimation bias | Musical intervals | Approximation | NOTES AND COMMENTS | Inference | Polynomials | Standard error | Estimators | Point estimators | Confidence interval | alternative asymptotics | robust inference | local polynomials | Regression discontinuity | bias correction | Bias correction | Alternative asymptotics | Robust inference | Local polynomials | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS
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Loading Rights1990, ISBN 9780824781293, xiii, 287
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2008, Quantitative applications in the social sciences, ISBN 9781412940726, Volume no. 07-152, xv, 107
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IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, 04/2016, Volume 63, Issue 4, pp. 822 - 832
The identification of the exact positions of the first and second heart sounds within a phonocardiogram (PCG), or heart sound segmentation, is an essential...
Heart | Pathology | Logistic regression | Heart sound segmentation | Hidden Markov models | Detectors | Electrocardiography | Phonocardiography | Logistics | logistic regression (LR) | 1ST | FETAL ECG EXTRACTION | ROBUST | phonocardiography (PCG) | ENGINEERING, BIOMEDICAL | ALGORITHM | DECOMPOSITION | NOISE | hidden Markov models (HMMs) | Signal Processing, Computer-Assisted | Markov Chains | Heart Sounds - physiology | Phonocardiography - methods | Humans | Databases, Factual | Sounds | Usage | Markov processes | Regression analysis | Research | Biomedical engineering
Heart | Pathology | Logistic regression | Heart sound segmentation | Hidden Markov models | Detectors | Electrocardiography | Phonocardiography | Logistics | logistic regression (LR) | 1ST | FETAL ECG EXTRACTION | ROBUST | phonocardiography (PCG) | ENGINEERING, BIOMEDICAL | ALGORITHM | DECOMPOSITION | NOISE | hidden Markov models (HMMs) | Signal Processing, Computer-Assisted | Markov Chains | Heart Sounds - physiology | Phonocardiography - methods | Humans | Databases, Factual | Sounds | Usage | Markov processes | Regression analysis | Research | Biomedical engineering
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Loading Rights2003, 1. Aufl., Wiley series in probability and statistics., ISBN 9780471488552, xiv, 329
WILEY-INTERSCIENCE PAPERBACK SERIESThe Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an...
Outliers (Statistics) | Least squares | Regression analysis
Outliers (Statistics) | Least squares | Regression analysis
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Pattern Recognition, ISSN 0031-3203, 2012, Volume 45, Issue 1, pp. 104 - 118
In this paper we address the problem of robust face recognition by formulating the pattern recognition task as a problem of robust estimation. Using a...
Robust estimation | Robust face recognition | Random pixel contamination | IMAGE | DISCRIMINANT-ANALYSIS | REPRESENTATION | ALGORITHMS | NONNEGATIVE MATRIX FACTORIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Analysis | Biometry | Algorithms | Face recognition | Noise | Images | Regression | Illumination | Pattern recognition | Invariants
Robust estimation | Robust face recognition | Random pixel contamination | IMAGE | DISCRIMINANT-ANALYSIS | REPRESENTATION | ALGORITHMS | NONNEGATIVE MATRIX FACTORIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Analysis | Biometry | Algorithms | Face recognition | Noise | Images | Regression | Illumination | Pattern recognition | Invariants
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Loading RightsAnnals of Operations Research, ISSN 0254-5330, 5/2019, Volume 276, Issue 1, pp. 191 - 210
Datasets with outliers pose a serious challenge in regression analysis. In this paper, a new regression method called relaxed support vector regression (RSVR)...
Outliers | Business and Management | Operations Research/Decision Theory | Relaxed support vector machines | Regression | Support vector regression | Theory of Computation | Combinatorics | Relaxed support vector regression | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | NEURAL-NETWORKS | CLASSIFICATION | SELECTION | Robust statistics | Logic programming | Regression analysis | Analysis | Datasets | Support vector machines | Economic models | Operations research | Data analysis | Robustness (mathematics) | Outliers (statistics) | Data sets
Outliers | Business and Management | Operations Research/Decision Theory | Relaxed support vector machines | Regression | Support vector regression | Theory of Computation | Combinatorics | Relaxed support vector regression | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | NEURAL-NETWORKS | CLASSIFICATION | SELECTION | Robust statistics | Logic programming | Regression analysis | Analysis | Datasets | Support vector machines | Economic models | Operations research | Data analysis | Robustness (mathematics) | Outliers (statistics) | Data sets
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Loading RightsIEEE Transactions on Information Theory, ISSN 0018-9448, 07/2010, Volume 56, Issue 7, pp. 3561 - 3574
Lasso, or l 1 regularized least squares, has been explored extensively for its remarkable sparsity properties. In this paper it is shown that the solution to...
Uncertainty | Robust stability | Statistical learning | Linear regression | Lasso | regularization | robustness | Vectors | sparsity | Least squares methods | regression | Information processing | Noise robustness | Protection | Kernel | stability | Stability | Sparsity | Regression | Robustness | Regularization | statistical learning | BASES | APPROXIMATION | COMPUTER SCIENCE, INFORMATION SYSTEMS | LEAST-SQUARES | ENGINEERING, ELECTRICAL & ELECTRONIC | SPARSE REPRESENTATION | DENSITY-FUNCTION | SELECTION | Least squares method | Physical properties | Density | Joints | Standards | Optimization
Uncertainty | Robust stability | Statistical learning | Linear regression | Lasso | regularization | robustness | Vectors | sparsity | Least squares methods | regression | Information processing | Noise robustness | Protection | Kernel | stability | Stability | Sparsity | Regression | Robustness | Regularization | statistical learning | BASES | APPROXIMATION | COMPUTER SCIENCE, INFORMATION SYSTEMS | LEAST-SQUARES | ENGINEERING, ELECTRICAL & ELECTRONIC | SPARSE REPRESENTATION | DENSITY-FUNCTION | SELECTION | Least squares method | Physical properties | Density | Joints | Standards | Optimization
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Loading Rights1987, Wiley series in probability and mathematical statistics. Applied probability and statistics, ISBN 9780471852339
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Loading RightsIEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 07/2012, Volume 23, Issue 7, pp. 1074 - 1086
Ordinal regression is commonly formulated as a multiclass problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal...
ordinal regression (OR) | transductive learning | Fasteners | Vectors | Convergence | Multiprotocol label switching | Training | ordinal classification | Motion pictures | Prediction algorithms | Cluster assumption | ordinal loss function | support vector machines (SVMs) | SUPPORT VECTOR MACHINES | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | CLASSIFICATION | COMPUTER SCIENCE, THEORY & METHODS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Robust statistics | Usage | Numerical analysis | Neural networks | Analysis | Regression analysis | Design and construction | Studies | Algorithms | Learning | Mathematical analysis | Regression | Abundance | Showcases | Mathematical models | Labels | Calibration | Computer Science - Learning
ordinal regression (OR) | transductive learning | Fasteners | Vectors | Convergence | Multiprotocol label switching | Training | ordinal classification | Motion pictures | Prediction algorithms | Cluster assumption | ordinal loss function | support vector machines (SVMs) | SUPPORT VECTOR MACHINES | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | CLASSIFICATION | COMPUTER SCIENCE, THEORY & METHODS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Robust statistics | Usage | Numerical analysis | Neural networks | Analysis | Regression analysis | Design and construction | Studies | Algorithms | Learning | Mathematical analysis | Regression | Abundance | Showcases | Mathematical models | Labels | Calibration | Computer Science - Learning
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Loading RightsIEEE Transactions on Image Processing, ISSN 1057-7149, 03/2017, Volume 26, Issue 3, pp. 1466 - 1481
In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However,...
Training | Computer vision | Computational modeling | image classification | Linear regression | Minimization | Robustness | Elastic-net regularization | Optimization | discriminative methods | linear regression | SPARSE REPRESENTATION | ROBUST FACE RECOGNITION | LEAST-SQUARES REGRESSION | CLASSIFICATION | ALGORITHMS | SELECTION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Computer-generated environments | Computer simulation | Machine vision | Analysis | Linear models (Statistics) | Research | Linear regression models | Regularization
Training | Computer vision | Computational modeling | image classification | Linear regression | Minimization | Robustness | Elastic-net regularization | Optimization | discriminative methods | linear regression | SPARSE REPRESENTATION | ROBUST FACE RECOGNITION | LEAST-SQUARES REGRESSION | CLASSIFICATION | ALGORITHMS | SELECTION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Computer-generated environments | Computer simulation | Machine vision | Analysis | Linear models (Statistics) | Research | Linear regression models | Regularization
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Loading RightsStatistics in Medicine, ISSN 0277-6715, 10/2019, Volume 38, Issue 23, pp. 4749 - 4760
Epidemiologic research often aims to estimate the association between a binary exposure and a binary outcome, while adjusting for a set of covariates (eg,...
conditional maximum likelihood | doubly robust estimation | conditional logistic regression | MEDICINE, RESEARCH & EXPERIMENTAL | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | MEDICAL INFORMATICS | CAUSAL INFERENCE | MATHEMATICAL & COMPUTATIONAL BIOLOGY | STATISTICS & PROBABILITY
conditional maximum likelihood | doubly robust estimation | conditional logistic regression | MEDICINE, RESEARCH & EXPERIMENTAL | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | MEDICAL INFORMATICS | CAUSAL INFERENCE | MATHEMATICAL & COMPUTATIONAL BIOLOGY | STATISTICS & PROBABILITY
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Loading RightsInformation Sciences, ISSN 0020-0255, 2011, Volume 181, Issue 19, pp. 4154 - 4174
In this paper we propose a robust fuzzy linear regression model based on the Least Median Squares–Weighted Least Squares (LMS–WLS) estimation procedure. The...
Outliers | Robust fuzzy multiple linear regression | LR fuzzy response variable | Least Median Squares (LMS) | Weighted Least Squares (WLS) | Goodness of fit | LINEAR-REGRESSION | LEAST-SQUARES REGRESSION | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | PROGRAMMING APPROACH | RANKING | MODELS | OUTLIERS DETECTION | SYSTEMS | OUTPUT DATA | INTERVALS | Analysis | Regression analysis | Performance evaluation | Fuzzy logic | Error analysis | Computer simulation | Least squares method | Regression | Fuzzy set theory | Fuzzy
Outliers | Robust fuzzy multiple linear regression | LR fuzzy response variable | Least Median Squares (LMS) | Weighted Least Squares (WLS) | Goodness of fit | LINEAR-REGRESSION | LEAST-SQUARES REGRESSION | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | PROGRAMMING APPROACH | RANKING | MODELS | OUTLIERS DETECTION | SYSTEMS | OUTPUT DATA | INTERVALS | Analysis | Regression analysis | Performance evaluation | Fuzzy logic | Error analysis | Computer simulation | Least squares method | Regression | Fuzzy set theory | Fuzzy
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Loading RightsBiometrika, ISSN 0006-3444, 09/2017, Volume 104, Issue 3, pp. 633 - 647
In high-dimensional multivariate regression problems, enforcing low rank in the coefficient matrix offers effective dimension reduction, which greatly...
Robust estimation | Non-asymptotic analysis | Sparsity | Low-rank matrix approximation | CONVEX RELAXATION | ALGORITHM | STATISTICS & PROBABILITY | GENERALIZED LINEAR-MODELS | VARIABLE SELECTION | NUCLEAR-NORM PENALIZATION | OPTIMAL RATES | ESTIMATORS | MATRICES | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY
Robust estimation | Non-asymptotic analysis | Sparsity | Low-rank matrix approximation | CONVEX RELAXATION | ALGORITHM | STATISTICS & PROBABILITY | GENERALIZED LINEAR-MODELS | VARIABLE SELECTION | NUCLEAR-NORM PENALIZATION | OPTIMAL RATES | ESTIMATORS | MATRICES | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY
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Loading RightsComputational Statistics and Data Analysis, ISSN 0167-9473, 09/2017, Volume 113, pp. 441 - 456
Sliced Inverse Regression (SIR) has been extensively used to reduce the dimension of the predictor space before performing regression. SIR is originally a...
Outliers | Dimension reduction | Robust estimation | Inverse regression | Generalized Student distribution | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | STATISTICS & PROBABILITY | Analysis | Algorithms | Statistics | Mathematics
Outliers | Dimension reduction | Robust estimation | Inverse regression | Generalized Student distribution | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | STATISTICS & PROBABILITY | Analysis | Algorithms | Statistics | Mathematics
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Loading RightsJournal of Multivariate Analysis, ISSN 0047-259X, 2004, Volume 91, Issue 1, pp. 74 - 89
The penalized least squares interpretation of the classical random effects estimator suggests a possible way forward for quantile regression models with a...
Penalty methods | L-statistics | Random effects | Robust estimation | Shrinkage | Quantile regression | Hierarchical models | random effects | robust estimation | ESTIMATORS | LASSO | quantile regression | hierarchical models | STATISTICS & PROBABILITY | penalty methods | LINEAR-MODEL | shrinkage | Quantile regression Penalty methods Shrinkage L-statistics Random effects Robust estimation Hierarchical models
Penalty methods | L-statistics | Random effects | Robust estimation | Shrinkage | Quantile regression | Hierarchical models | random effects | robust estimation | ESTIMATORS | LASSO | quantile regression | hierarchical models | STATISTICS & PROBABILITY | penalty methods | LINEAR-MODEL | shrinkage | Quantile regression Penalty methods Shrinkage L-statistics Random effects Robust estimation Hierarchical models
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Loading RightsIEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 05/2013, Volume 35, Issue 5, pp. 1149 - 1163
We propose a new algorithm to detect facial points in frontal and near-frontal face images. It combines a regression-based approach with a probabilistic...
Training | Support vector machines | support vector regression | Shape | Prediction algorithms | Feature extraction | Vectors | object detection | Face | probabilistic graphical networks | Facial point detection | DATABASE | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Regression Analysis | Humans | Face - anatomy & histology | Image Processing, Computer-Assisted - methods | Support Vector Machine | Biometric Identification - methods | Databases, Factual | Robust statistics | Usage | Analysis | Approximation theory | Regression analysis | Mathematical optimization | Methods
Training | Support vector machines | support vector regression | Shape | Prediction algorithms | Feature extraction | Vectors | object detection | Face | probabilistic graphical networks | Facial point detection | DATABASE | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Regression Analysis | Humans | Face - anatomy & histology | Image Processing, Computer-Assisted - methods | Support Vector Machine | Biometric Identification - methods | Databases, Factual | Robust statistics | Usage | Analysis | Approximation theory | Regression analysis | Mathematical optimization | Methods
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