0000000000400633

AUTHOR

Hector Gonzalez

showing 3 related works from this author

Accelerated Proximal Gradient Descent in Metric Learning for Kernel Regression

2018

The purpose of this paper is to learn a specific distance function for the Nadayara Watson estimator to be applied as a non-linear classifier. The idea of transforming the predictor variables and learning a kernel function based on Mahalanobis pseudo distance througth an low rank structure in the distance function will help us to lead the development of this problem. In context of metric learning for kernel regression, we introduce an Accelerated Proximal Gradient to solve the non-convex optimization problem with better convergence rate than gradient descent. An extensive experiment and the corresponding discussion tries to show that our strategie its a competitive solution in relation to p…

Mahalanobis distanceOptimization problembusiness.industryComputer scienceEstimator02 engineering and technology010501 environmental sciences01 natural sciencesRate of convergenceMetric (mathematics)0202 electrical engineering electronic engineering information engineeringKernel regression020201 artificial intelligence & image processingArtificial intelligencebusinessGradient descentAlgorithmClassifier (UML)0105 earth and related environmental sciences
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Improving Nearest Neighbor Based Multi-target Prediction Through Metric Learning

2017

The purpose of this work is to learn specific distance functions to be applied for multi-target regression problems using nearest neighbors. The idea of preserving the order relation between input and output vectors considering their corresponding distances is used along a maximal margin criterion to formulate a specific metric learning problem. Extensive experiments and the corresponding discussion try to put forward the advantages of the proposed algorithm that can be considered as a generalization of previously proposed approaches. Preliminary results suggest that this line of work can lead to very competitive algorithms with convenient properties.

Cover treeComputer scienceNearest neighbor search0211 other engineering and technologies02 engineering and technologyk-nearest neighbors algorithmBest bin firstMargin (machine learning)Nearest-neighbor chain algorithmMetric (mathematics)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingAlgorithmLarge margin nearest neighbor021101 geological & geomatics engineering
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Generalized Multitarget Linear Regression with Output Dependence Estimation

2019

Multitarget regression has recently received attention in the context of modern, large-scale problems in which finding good enough solutions in a timely manner is crucial. Different proposed alternatives use a combination of regularizers that lead to different ways of solving the problem. In this work, we introduce a general formulation with several regularizers. This leads to a biconvex minimization problem and we use an alternating procedure with accelerated proximal gradient steps to solve it. We show that our formulation is equivalent but more efficient than some previously proposed approaches. Moreover, we introduce two new variants. The experimental validation carried out, suggests th…

Mathematical optimizationComputer scienceMinimization problemContext (language use)02 engineering and technologyExperimental validation01 natural sciencesRegression010104 statistics & probabilityLinear regression0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0101 mathematicsRegression problems
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