Ebook: Discrete Probability and Algorithms
- Tags: Combinatorics, Probability Theory and Stochastic Processes, Statistics general
- Series: The IMA Volumes in Mathematics and its Applications 72
- Year: 1995
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much longer. The papers in this volume address the latest developments in this active field. They are from the IMA Workshops "Probability and Algorithms" and "The Finite Markov Chain Renaissance." They represent the current thinking of many of the world's leading experts in the field.
Researchers and graduate students in probability, computer science, combinatorics, and optimization theory will all be interested in this collection of articles. The techniques developed and surveyed in this volume are still undergoing rapid development, and many of the articles of the collection offer an expositionally pleasant entree into a research area of growing importance.
Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much longer. The papers in this volume address the latest developments in this active field. They are from the IMA Workshops "Probability and Algorithms" and "The Finite Markov Chain Renaissance." They represent the current thinking of many of the world's leading experts in the field.
Researchers and graduate students in probability, computer science, combinatorics, and optimization theory will all be interested in this collection of articles. The techniques developed and surveyed in this volume are still undergoing rapid development, and many of the articles of the collection offer an expositionally pleasant entree into a research area of growing importance.
Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much longer. The papers in this volume address the latest developments in this active field. They are from the IMA Workshops "Probability and Algorithms" and "The Finite Markov Chain Renaissance." They represent the current thinking of many of the world's leading experts in the field.
Researchers and graduate students in probability, computer science, combinatorics, and optimization theory will all be interested in this collection of articles. The techniques developed and surveyed in this volume are still undergoing rapid development, and many of the articles of the collection offer an expositionally pleasant entree into a research area of growing importance.
Content:
Front Matter....Pages i-xvii
On Simulating a Markov Chain Stationary Distribution when Transition Probabilities are Unknown....Pages 1-9
A Note on Network Reliability....Pages 11-14
Rectangular Arrays with Fixed Margins....Pages 15-41
Three Examples of Monte-Carlo Markov Chains: At the Interface Between Statistical Computing, Computer Science, and Statistical Mechanics....Pages 43-56
The Move-To-Front Rule for Self-Organizing Lists with Markov Dependent Requests....Pages 57-80
The Asymptotic Lower Bound on the Diagonal Ramsey Numbers: A Closer Look....Pages 81-94
Random Walks and Undirected Graph Connectivity: A Survey....Pages 95-101
Sidon Sets with Small Gaps....Pages 103-109
Variations on the Monotone Subsequence Theme of Erd?s and Szekeres....Pages 111-131
Randomised Approximation Schemes for Tutte-Gr?thendieck Invariants....Pages 133-148
Quasi-Additive Euclidean Functionals....Pages 149-158
Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much longer. The papers in this volume address the latest developments in this active field. They are from the IMA Workshops "Probability and Algorithms" and "The Finite Markov Chain Renaissance." They represent the current thinking of many of the world's leading experts in the field.
Researchers and graduate students in probability, computer science, combinatorics, and optimization theory will all be interested in this collection of articles. The techniques developed and surveyed in this volume are still undergoing rapid development, and many of the articles of the collection offer an expositionally pleasant entree into a research area of growing importance.
Content:
Front Matter....Pages i-xvii
On Simulating a Markov Chain Stationary Distribution when Transition Probabilities are Unknown....Pages 1-9
A Note on Network Reliability....Pages 11-14
Rectangular Arrays with Fixed Margins....Pages 15-41
Three Examples of Monte-Carlo Markov Chains: At the Interface Between Statistical Computing, Computer Science, and Statistical Mechanics....Pages 43-56
The Move-To-Front Rule for Self-Organizing Lists with Markov Dependent Requests....Pages 57-80
The Asymptotic Lower Bound on the Diagonal Ramsey Numbers: A Closer Look....Pages 81-94
Random Walks and Undirected Graph Connectivity: A Survey....Pages 95-101
Sidon Sets with Small Gaps....Pages 103-109
Variations on the Monotone Subsequence Theme of Erd?s and Szekeres....Pages 111-131
Randomised Approximation Schemes for Tutte-Gr?thendieck Invariants....Pages 133-148
Quasi-Additive Euclidean Functionals....Pages 149-158
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