Machine LearningLe Thi HA, Le Hoai M, Pham Dinh T (2015a) Feature selection in machine learning: an exact penalty approach using a difference of convex function algorithm. Mach Learn 101:163–186 MathSciNetLE T
We propose a combination of machine learning and flux limiting for property-preserving subgrid scale modeling in the context of flux-limited finite volume methods for the one-dimensional shallow-water equations. The numerical fluxes of a conservative target scheme are fitted to the coarse-mesh ...
这本书是由 Michael Nielsen 和 Isaac Schreiber 合著的，于2019年由MIT出版社出版。该书是机器学习领域中关于非凸优化问题的经典著作之一，主要介绍了一些非凸优化算法以及如何求解非凸优化问题。书中主要讲了两种非凸情况：一是目标函数是凸的，约束集合不是凸的，即 f(x) 凸，C 非凸；二是目标函数不是凸的...
In the bandit setting, since only the function value is available to the player instead of the gradient, the problem becomes more challenging. Fortunately, Agarwal et al. (2010) have proposed to approximate the gradient by querying the function at two points and n+1 points. To avoid the cos...
layer feedforward networks (SLFNs) with randomly generated additive or radial basis function (RBF) hidden nodes (according to any continuous sampling distribution) can work as universal approximators and the resulting incremental extreme learning machine (I-ELM) outperforms many popular learning ...
A function, f(x), is concave if f(x) is convex. Strict convexity (and strict concavity) are obtained by replacing with < Robust Control & Convex Optimization 5: Convex optimization !13 Simple examples: Convex functions: Concave functions: A ne functions, f(x) = ax +b for any a, b...
These methods might be useful in the core of your own implementation of a machine learning algorithm. You may want to implement your own algorithm tuning scheme to optimize the parameters of a model for some cost function. A good example may be the case where you want to optimize the hyper...
Operator Theory for Analysis of Convex Optimization Methods in Machine Learning(机器学习凸优化方法分析的算子理论) 热度: 凸优化_Convex_Optimization 热度: Convex Optimization in Signal:在信号的凸优化 热度: ConvexOptimization ConvexOptimization StephenBoyd ...
Foundations and Trends® in Machine Learning(共66册), 这套丛书还有 《Kernels for Vector-Valued Functions》《Model-based Reinforcement Learning》《A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists》《On the Concentration Properties of Interacting Particle Processes》《Spectral Me...
May 10, 2023|research areaMethods and Algorithms,research areaPrivacy|conferenceICML *= Equal Contributors We study the relationship between two desiderata of algorithms in statistical inference and machine learning—differential privacy and robustness to adversarial data corruptions. Their conceptual similarity...