Results 21 to 30 of about 163,423 (274)
Frontiers in Medicine, 2022 BackgroundObtaining an ideal vault is crucial in the implantable collamer lens (ICL) surgery. Prediction of the vault value is difficult since it requires the integration of multiple factors.
Zhikun Yang +7 more
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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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On Convex Least Squares Estimation when the Truth is Linear [PDF]
, 2015 We prove that the convex least squares estimator (LSE) attains a $n^{-1/2}$ pointwise rate of convergence in any region where the truth is linear. In addition, the asymptotic distribution can be characterized by a modified invelope process.
Chen, Yining, Wellner, Jon A.
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Private Multiplicative Weights Beyond Linear Queries [PDF]
, 2015 A wide variety of fundamental data analyses in machine learning, such as linear and logistic regression, require minimizing a convex function defined by the data.
Bassily R. +8 more
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Testing convex hypotheses on the mean of a Gaussian vector. Application to testing qualitative hypotheses on a regression function [PDF]
, 2005 In this paper we propose a general methodology, based on multiple testing, for testing that the mean of a Gaussian vector in R^n belongs to a convex set. We show that the test achieves its nominal level, and characterize a class of vectors over which the
Baraud, Yannick +2 more
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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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CoCoA: A General Framework for Communication-Efficient Distributed Optimization [PDF]
, 2017 The scale of modern datasets necessitates the development of efficient distributed optimization methods for machine learning. We present a general-purpose framework for distributed computing environments, CoCoA, that has an efficient communication scheme
Forte, Simone +5 more
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