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Statistical Inference via Convex Optimization

optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an;

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Convex Optimization In Signal Processing And Communications

Over the past two decades there have been significant advances in the field of optimization. In particular, convex optimization has emerged;

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Convex Optimization

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and;

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Convex Optimization Euclidean Distance Geometry 2e

Convex Analysis is an emerging calculus of inequalities while Convex Optimization is its application. Analysis is the domain of the;

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Markov Logic

resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been;

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Optimality Conditions in Convex Optimization

Optimality Conditions in Convex Optimization explores an important and central issue in the field of convex optimization: optimality;

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Convex Optimization & Euclidean Distance Geometry

Optimization is the science of making a best choice in the face of conflicting requirements. Any convex optimization problem has geometric;

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Convex Optimization

This book provides easy access to the basic principles and methods for solving constrained and unconstrained convex optimization problems;

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Selected Applications of Convex Optimization

This book focuses on the applications of convex optimization and highlights several topics, including support vector machines, parameter;

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Convex Optimization for Signal Processing and Communications

Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications provides fundamental background knowledge;

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Convex Optimization for Signal Processing and Communications

Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications provides fundamental background knowledge;

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Convex Analysis for Optimization

This textbook offers graduate students a concise introduction to the classic notions of convex optimization. Written in a highly accessible;

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Convex Analysis for Optimization

This textbook offers graduate students a concise introduction to the classic notions of convex optimization. Written in a highly accessible;

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Discrete Convex Analysis

Discrete Convex Analysis is a novel paradigm for discrete optimization that combines the ideas in continuous optimization (convex analysis;

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Swarm Intelligence Methods for Statistical Regression

to noisy data in order to capture meaningful patterns. This can often result in challenging non-linear and non-convex global optimization;

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Swarm Intelligence Methods for Statistical Regression

to noisy data in order to capture meaningful patterns. This can often result in challenging non-linear and non-convex global optimization;

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An Easy Path to Convex Analysis and Applications

Convex optimization has an increasing impact on many areas of mathematics, applied sciences, and practical applications. It is now being;

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Convex Optimization of Power Systems

Optimization is ubiquitous in power system engineering. Drawing on powerful, modern tools from convex optimization, this rigorous;

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Algorithms for Convex Optimization

In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous;

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Algorithms for Convex Optimization

In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous;

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Optimal Statistical Inference in Financial Engineering

option pricing theory, the statistical estimation for portfolio coefficients, and value-at-risk (VaR) problems via residual empirical return;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Lectures on Modern Convex Optimization

Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and;

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Machine Learning

convex optimization, including a chapter on stochastic approximation and the gradient descent family of algorithms, presenting related online;

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Markov Logic

resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been;

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Even Convexity and Optimization

convex sets. The book introduces their application to convex optimization. Particular attention is paid to evenly convex polyhedra and finite;

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