Stochastic Optimization Authors: Johannes Josef SchneiderScott Kirkpatrick The search for optimal solutions pervades our daily lives. From the scientific point of view, optimization procedures play an eminent role whenever exact solutions to a given problem are not at hand or a compromise has to be sought, e.g. to obtain a sufficiently accurate solution within a given amount of time. This book addresses stochastic optimization procedures in a broad manner, giving an overview of the most relevant optimization philosophies in the first part. The second part deals with benchmark problems in depth, by applying in sequence a selection of optimization procedures to them. While having primarily scientists and students from the physical and engineering sciences in mind, this book addresses the larger community of all those wishing to learn about stochastic optimization techniques and how to use them.

Stochastic-Modeling模式识别

《随机微积分应用于金融学概论》 此文档仅用于学习交流使用，请勿用做商业用途，违者后果自负

A first course in stochastic processes (2ed., AP, 1975)Karlin S., Taylor

深度学习ADAM算法，分享给大家学习。 We introduce Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments. The method is straightforward to implement, is computationally efficient, has little memory requirements, is invariant to diagonal rescaling of the gradients, and is well suited for problems that are large in terms of data and/or parameters. The method is also appropriate for non-stationary objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive interpretations and typically require little tuning. Some connections to related algorithms, on which Adam was inspired, are discussed. We also analyze the theoretical convergence properties of the algorithm and provide a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework. Empirical results demonstrate that Adam works well in practice and compares favorably to other stochastic optimization methods. Finally, we discuss AdaMax, a variant of Adam based on the infinity norm.

Stochastic Geometry for Wireless Networks ，带详细书签, 作者 Martin Haenggi 友情奉上 :)

Introduction to Stochastic Processes 随机过程介绍

这是一本关于随机规划比较全面的书！比较难，不太容易啃，但是读了之后收获很大。这是高清版的！

随机过程，英文版，第二版，Sheldoen Ross 编著 《随机过程(原书[第2版)》从概率的角度而不是分析的角度来看待随机过程，书中介绍了随机过程的基本理论，包括Poisson过程、Markov链、鞅、 Brown运动、随机序关系、Poisson逼近等，并阐明这些理论在各领域的应用

A Second Course in Stochastic Processes - Karlin & Taylor(1981)