Exact algorithms for dealing with geometric objects are complicated, hard to implement in practice, and slow. Over the last 20 years a theory of geometric approximation algorithms has emerged. These algorithms tend to be simple, fast, and more robust than their exact counterparts. This book is the first to cover geometric approximation algorithms in detail. In addition, more traditional computational geometry techniques that are widely used in developing such algorithms, like sampling, linear programming, etc., are also surveyed. Other topics covered include approximate nearest-neighbor search, shape approximation, coresets, dimension reduction, and embeddings. The topics covered are relatively independent and are supplemented by exercises....
At the core of successful manipulation and computation over large geometric data is the notion of ap...
At the core of successful manipulation and computation over large geometric data is the notion of ap...
We adapt an algorithm for computing a deterministic sample in a set system to compute εapproximation...
Computational geometry emerged from the field of algorithms design and anal ysis in the late 1970s....
Computational geometry emerged from the field of algorithms design and anal ysis in the late 1970s....
The computer--aided solution to algorithmic problems is becoming more and more important in various ...
The computer--aided solution to algorithmic problems is becoming more and more important in various ...
A fundamental task of computational geometry is identifying concepts, properties and techniques whic...
Research Focus: My thesis research was to develop approximation algorithms for computational geometr...
In this survey paper, we present an overview of approximation algorithms that are designed for art g...
<p>Large scale geometric data is ubiquitous. In this dissertation, we design algorithms and data str...
The computer--aided solution to algorithmic problems is becoming more and more important in various ...
The paradigm of coresets has recently emerged as a powerful tool for efficiently approximating vario...
Introduction This is a follow up on the previous Chapter dealing with geometric problems and their ...
In this survey we consider geometric techniques which have been used to measure the similarity or di...
At the core of successful manipulation and computation over large geometric data is the notion of ap...
At the core of successful manipulation and computation over large geometric data is the notion of ap...
We adapt an algorithm for computing a deterministic sample in a set system to compute εapproximation...
Computational geometry emerged from the field of algorithms design and anal ysis in the late 1970s....
Computational geometry emerged from the field of algorithms design and anal ysis in the late 1970s....
The computer--aided solution to algorithmic problems is becoming more and more important in various ...
The computer--aided solution to algorithmic problems is becoming more and more important in various ...
A fundamental task of computational geometry is identifying concepts, properties and techniques whic...
Research Focus: My thesis research was to develop approximation algorithms for computational geometr...
In this survey paper, we present an overview of approximation algorithms that are designed for art g...
<p>Large scale geometric data is ubiquitous. In this dissertation, we design algorithms and data str...
The computer--aided solution to algorithmic problems is becoming more and more important in various ...
The paradigm of coresets has recently emerged as a powerful tool for efficiently approximating vario...
Introduction This is a follow up on the previous Chapter dealing with geometric problems and their ...
In this survey we consider geometric techniques which have been used to measure the similarity or di...
At the core of successful manipulation and computation over large geometric data is the notion of ap...
At the core of successful manipulation and computation over large geometric data is the notion of ap...
We adapt an algorithm for computing a deterministic sample in a set system to compute εapproximation...