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Optimization for Machine Learning (Neural Information Processing series)
Optimization for Machine Learning (Neural Information Processing series)
The intersection of interests between machine learning and optimization has engaged many leading researchers in both communities for some years now. Both are vital and growing fields, and the areas of shared interest are expanding too. This volume collects contributions from many researchers who have been a part of these...
Markovian Demand Inventory Models (International Series in Operations Research & Management Science)
Markovian Demand Inventory Models (International Series in Operations Research & Management Science)

Inventory management is concerned with matching supply with demand and a central problem in Operations Management. The problem is to find the amount to be produced or purchased in order to maximize the total expected profit or minimize the total expected cost. Over the past two decades, several variations of the formula appeared, mostly in trade...

Introduction to Stochastic Integration (Modern Birkhäuser Classics)
Introduction to Stochastic Integration (Modern Birkhäuser Classics)

A highly readable introduction to stochastic integration and stochastic differential equations, this book combines developments of the basic theory with applications. It is written in a style suitable for the text of a graduate course in stochastic calculus, following a course in probability.

Using the modern approach, the...

Signal Detection And Estimation
Signal Detection And Estimation
This book provides an overview and introduction to signal detection and estimation. The book contains numerous examples solved in detail. Since some material on signal detection could be very complex and require a lot of background in engineering math, a chapter and various sections to cover such background are included, so that one can easily...
Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE (Fields Institute Monographs)
Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE (Fields Institute Monographs)

​This book collects some recent developments in stochastic control theory with applications to financial mathematics. We first address standard stochastic control problems from the viewpoint of the recently developed weak dynamic programming principle. A special emphasis is put on the regularity issues and, in particular, on the behavior...

Theory of Neural Information Processing Systems
Theory of Neural Information Processing Systems
Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative discipline, including mathematics, computer science, physics, engineering or biology, and has been...
Probabilistic and Statistical Methods in Cryptology: An Introduction by Selected Topics
Probabilistic and Statistical Methods in Cryptology: An Introduction by Selected Topics
From the reviews:

"This book presents a large number of probabilistic aspects of cryptographic systems . All the classical statistical tests on random sequences are motivated and precisely detailed here. This book is surely a valuable companion to the NIST standard reference ." (Jérémie Bourdon, Mathematical...

Modeling Online Auctions (Statistics in Practice)
Modeling Online Auctions (Statistics in Practice)

Explore cutting-edge statistical methodologies for collecting, analyzing, and modeling online auction data

Online auctions are an increasingly important marketplace, as the new mechanisms and formats underlying these auctions have enabled the capturing and recording of large amounts of bidding data that are used to make...

From Gestalt Theory to Image Analysis: A Probabilistic Approach (Interdisciplinary Applied Mathematics)
From Gestalt Theory to Image Analysis: A Probabilistic Approach (Interdisciplinary Applied Mathematics)
The theory in these notes was taught between 2002 and 2005 at the graduate schools of Ecole Normale Sup´erieure de Cachan, Ecole Polytechnique de Palaiseau, Universitat Pompeu Fabra, Barcelona, Universitat de les Illes of Balears, Palma, and University of California at Los Angeles. It is also being taught by Andr`es Almansa...
Basic Concepts in Computational Physics
Basic Concepts in Computational Physics

With the development of ever more powerful computers a new branch of physics and engineering evolved over the last few decades: Computer Simulation or Computational Physics. It serves two main purposes:

- Solution of complex mathematical problems such as, differential equations, minimization/optimization, or high-dimensional...

Principles of Artificial Neural Networks (Advanced Series in Circuits and Systems)
Principles of Artificial Neural Networks (Advanced Series in Circuits and Systems)
Artificial neural networks are, as their name indicates, computational networks which attempt to simulate, in a gross manner, the networks of nerve cell (neurons) of the biological (human or animal) central nervous system. This simulation is a gross cell-by-cell (neuron-by-neuron, element-by-element) simulation. It borrows from the...
An Elementary Introduction to Mathematical Finance
An Elementary Introduction to Mathematical Finance

This textbook on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability, Sheldon M. Ross offers clear, simple explanations of arbitrage, the Black-Scholes option pricing formula,...

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