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نتیجه جستجو - Stochastic processes

تعداد مقالات یافته شده: 3
ردیف عنوان نوع
1 Law of large numbers and central limit theorem for a class of pure jump Markov process
قانون اعداد بزرگ و قضیه حد مرکزی برای یک کلاس از فرآیند پرش خالص مارکوف-2020
This paper studies the law of large numbers (LLN) and central limit theorem (TCL) for a class of scaled pure jump Markov processes where the processes state variables are in Rdand where jump amplitudes depend on the state variables. Non-explosion property and semi-martingale decomposition are studied first for a class of stochastic processes, allowing to study in a second step these same properties for the scaled pure jump Markov processes we consider characterized by infinitely small jumps and rapid jumps rates. Then, asymptotic behavior is derived and convergence results are obtained.
Keywords: Sacled processes | Pure jump Markov processes | LLN | TCL | Population dynamics | Interacting particles
مقاله انگلیسی
2 Nomadic Computing for Big Data Analytics
محاسبات Nomadic برای تحلیل داده های بزرگ-2016
oday’s applications often contain datasets that are too big to fit in a single comput er’s main memory. Analyzing these massive datasets will require scalable and sophisti- -cated machine-learning methods. Two commonly used approaches are stochastic optimization and inference algorithms,1 which process one data point at a time; and distributed computing based on the MapReduce framework,2 where the computation proceeds in iterations, with a master processor distributing the computation to slaves at each iteration. Although stochastic optimization and inference algorithms are effective for largescale machine learning, they are inherently sequential.On the other hand, MapReduce-based algorithms suffer from the curse of the last reducer, in that the slaves must wait for the slowest processor to finish before moving on to the next computational iteration.
Keywords: Stochastic processes | Charge coupled devices | Scalability | Big data | Motion pictures | Inference algorithms | Partitioning algorithms
مقاله انگلیسی
3 Stochastic Processes – Inference Theory
فرآیندهای تصادفی - نظریه استنتاج-2015
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
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