Titlebook: Mathematical Foundations of Big Data Analytics; Vladimir Shikhman,David Müller Textbook 2021 Springer-Verlag GmbH Germany, part of Springe

Sedative

ostracize

Online Learning,we consider pricing of goods, portfolio selection, or expert advice, a common feature emerges: huge amounts of dynamic data need to be understood and quickly processed. In order to cope with this issue, the paradigm of . has been introduced. According to the latter, data becomes available in a seque

是他笨

Recommendation Systems,cording to the prediction. Typical recommendation services include videos and movies as for Netflix, YouTube, and Spotify, consumption goods as for Amazon, pieces of social content as for Facebook and Twitter. Recommendation systems are supposed to contribute to the management of the information ove

傳授知識(shí)

暴露他抗議

Handedness

首創(chuàng)精神

Sparse Recovery,el complexity, the concept of sparsity is widely used over last decades. . refers in this context to the requirement that most of the model parameters are equal or close to zero. As a relevant application, we mention the . from econometrics, where zero entries correspond to irrelevant features. Anot

Isometric

Neural Networks, means of weights. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by weights and summed up. This aggregation corresponds to taking linear combinations. Finally, an activation function controls the amplitude of the outpu

Yag-Capsulotomy

geometrician