Keywords: computational geometry
Displaying 1-6 of 6 results.
Advanced Algorithms, Fall 1999
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| Type: | Course Related Materials |
Abstract: A first-year graduate course in algorithms. Emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Data structures. Network flows. Linear programming. Computational geometry. Approximation algorithms.
Advanced Algorithms, Fall 2005
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Abstract: This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic ... More »
Foundations of Software Engineering, Fall 2000
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Abstract: Foundations subject in modern software development techniques for engineering and information technology. Covers the design and development of component-based software (using C# and .NET); data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web ... More »
Geometric Combinatorics, Fall 2005
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Abstract: Introduction to discrete and computational geometry. Topics covered: planar graphs, geometric graphs, the theory of crossings, extremal graph theory, arrangements of curves and points in the plane (mainly pseudolines and pseudocircles), problems involving distances, Gallai-Sylvester-type problems, Davenport-Schinzel ... More »
Introduction to Algorithms (SMA 5503), Fall 2004
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| Type: | Course Related Materials |
Abstract: Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic ... More »
Introduction to Algorithms (SMA 5503), Fall 2005
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| Type: | Course Related Materials |
Abstract: Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic ... More »
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