Results 31 to 40 of about 27,189 (192)
Deep Successive Convex Approximation for Image Super-Resolution
Mathematics, 2023 Image super-resolution (SR), as one of the classic image processing issues, has attracted increasing attention from researchers. As a highly ill-conditioned, non-convex optimization issue, it is difficult for image SR to restore a high-resolution (HR ...
Xiaohui Li, Jinpeng Wang, Xinbo Liu
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Drawing Area-Proportional Venn-3 Diagrams with Convex Polygons [PDF]
, 2010 Area-proportional Venn diagrams are a popular way of visualizing the relationships between data sets, where the set intersections have a specified numerical value. In these diagrams, the areas of the regions are in proportion to the given values. Venn-3,
Howse, John +7 more
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Adaptive Sampling for Convex Regression
CoRR, 2018 In this paper, we introduce the first principled adaptive-sampling procedure for learning a convex function in the $L_\infty$ norm, a problem that arises often in the behavioral and social sciences. We present a function-specific measure of complexity and use it to prove that, for each convex function $f_{\star}$, our algorithm nearly attains the ...
Max Simchowitz +3 more
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Essays on Convex Regression and Frontier Estimation
, 2022 Convex regression is increasingly popular in economics, finance, operations research, machine learning, and statistics. In the productivity and efficiency analysis field, convex regression and its latest development have bridged the long-standing gap ...
Dai, Sheng
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Multivariate convex regression with adaptive partitioning
J. Mach. Learn. Res., 2011 We propose a new, nonparametric method for multivariate regression subject to convexity or concavity constraints on the response function. Convexity constraints are common in economics, statistics, operations research, financial engineering and optimization, but there is currently no multivariate method that is computationally feasible for more than a ...
Lauren Hannah, David B. Dunson
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Wind Speed Interval Prediction Based on the Hybrid Ensemble Model With Biased Convex Cost Function
Frontiers in Energy Research, 2022 This study proposes a combination interval prediction based hybrid ensemble (CIPE) model for short-term wind speed prediction. The combination interval prediction (CIP) model employs the extreme learning machine (ELM) as the predictor with a biased ...
Huan Long, Runhao Geng, Chen Zhang
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Twin Support Vector Regression Model Based on Heteroscedastic Gaussian Noise and Its Application
IEEE Access, 2022 The main purpose of twin support vector regression (TSVR) is to find linear or nonlinear relationships in sample data, and then predict future data. TSVR is the decomposition of a large convex quadratic programming problem into two small convex quadratic
Shiguang Zhang +3 more
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The Learning Rates of Regularized Regression Based on Reproducing Kernel Banach Spaces
Abstract and Applied Analysis, 2013 We study the convergence behavior of regularized regression based on reproducing kernel Banach spaces (RKBSs). The convex inequality of uniform convex Banach spaces is used to show the robustness of the optimal solution with respect to the distributions.
Baohuai Sheng, Peixin Ye
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Journal of Inequalities and Applications, 2021 In this work, we introduce a new accelerated algorithm using a linesearch technique for solving convex minimization problems in the form of a summation of two lower semicontinuous convex functions.
Panitarn Sarnmeta +3 more
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Convex Factorization Machine for Regression
CoRR, 2015 We propose the convex factorization machine (CFM), which is a convex variant of the widely used Factorization Machines (FMs). Specifically, we employ a linear+quadratic model and regularize the linear term with the $\ell_2$-regularizer and the quadratic term with the trace norm regularizer.
Yamada, Makoto +8 more
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