Q&A for students, researchers and practitioners of computer science. Stack Exchange network consists of 176 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.. Visit Stack Exchange Artificial neural networks (ANN) are general-purpose self-learning systems that grew out of the cognitive and brain science disciplines for approximating the way information is being processed . Instead of analyzing the vertical relationship between underlying cause and its derived effect, ANN learning models focus on how effects reproduce themselves horizontally and what this reveals ... Differential machine learning combines automatic adjoint differentiation (AAD) with modern machine learning (ML) in the context of risk management of financial Derivatives. We introduce novel algorithms for training fast, accurate pricing and risk approximations, online, in real-time, with convergence guarantees. Our machinery is applicable to arbitrary Derivatives instruments or trading books ... We consider upper bounds (there exist lower bounds as well (Vapnik and Chervonenkis, 1974); however, they are not as important for controlling the learning processes as the upper bounds). View ... Neural 28 - Free download as PDF File (.pdf), Text File (.txt) or read online for free. neural networks (1989). An empirical comparison of pattern recognition, neural nets, and machine learning classi methods. In ... (1989). Learnability and the vapnik-chervonenkis dimension. (1990). Learning logical de from relations. (2004). Learning Ranking of Learning Algorithms. (1992). Learning with continuous Classes. (2000). Linkage problem, distribution estimation, and bayesian networks. (2005 ... Oneto L, Anguita D and Ridella S (2016) A local Vapnik-Chervonenkis complexity, Neural Networks, 82:C, (62-75), Online publication date: 1-Oct-2016. Utkin L, Chekh A and Zhuk Y (2016) Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels, Neural Networks, 80 :C , (53-66), Online publication date: 1-Aug-2016 .
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