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6.046J Introduction to Algorithms (SMA 5503) (MIT) 6.046J Introduction to Algorithms (SMA 5503) (MIT)

Description

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms). This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Subjects

algorithms | algorithms | efficient algorithms | efficient algorithms | sorting | sorting | search trees | search trees | heaps | heaps | hashing | hashing | divide-and-conquer | divide-and-conquer | dynamic programming | dynamic programming | amortized analysis | amortized analysis | graph algorithms | graph algorithms | shortest paths | shortest paths | network flow | network flow | computational geometry | computational geometry | number-theoretic algorithms | number-theoretic algorithms | polynomial and matrix calculations | polynomial and matrix calculations | caching | caching | parallel computing | parallel computing | SMA 5503 | SMA 5503 | 6.046 | 6.046

License

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6.854J Advanced Algorithms (MIT) 6.854J Advanced Algorithms (MIT)

Description

6.854J is a first-year graduate course in algorithms, continuing where 6.046J left off. The course emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Topics include: data structures, network flows, linear programming, computational geometry, approximation algorithms. 6.854J is a first-year graduate course in algorithms, continuing where 6.046J left off. The course emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Topics include: data structures, network flows, linear programming, computational geometry, approximation algorithms.

Subjects

algorithm design and analysis | algorithm design and analysis | algorithms | algorithms | fundamental algorithms | fundamental algorithms | advanced methods of algorithmic design | advanced methods of algorithmic design | analysis | analysis | implementation | implementation | data structures | data structures | network flows | network flows | linear programming | linear programming | computational geometry | computational geometry | approximation algorithms | approximation algorithms | algorithmic design | algorithmic design | algorithmic analysis | algorithmic analysis | string algorithms | string algorithms | maximum flows | maximum flows | online algorithms | online algorithms | scheduling | scheduling | external memory algorithms | external memory algorithms | 6.854 | 6.854 | 18.415 | 18.415

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.046J Introduction to Algorithms (MIT) 6.046J Introduction to Algorithms (MIT)

Description

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing. This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

Subjects

algorithms | algorithms | efficient algorithms | efficient algorithms | sorting | sorting | search trees | search trees | heaps | heaps | hashing | hashing | divide-and-conquer | divide-and-conquer | dynamic programming | dynamic programming | amortized analysis | amortized analysis | graph algorithms | graph algorithms | shortest paths | shortest paths | network flow | network flow | computational geometry | computational geometry | number-theoretic algorithms | number-theoretic algorithms | polynomial and matrix calculations | polynomial and matrix calculations | caching | caching | parallel computing | parallel computing | 6.046 | 6.046 | 18.410 | 18.410

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.046J Introduction to Algorithms (SMA 5503) (MIT) 6.046J Introduction to Algorithms (SMA 5503) (MIT)

Description

Includes audio/video content: AV lectures. This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms). Includes audio/video content: AV lectures. This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Subjects

algorithms | algorithms | efficient algorithms | efficient algorithms | sorting | sorting | search trees | search trees | heaps | heaps | hashing | hashing | divide-and-conquer | divide-and-conquer | dynamic programming | dynamic programming | amortized analysis | amortized analysis | graph algorithms | graph algorithms | shortest paths | shortest paths | network flow | network flow | computational geometry | computational geometry | number-theoretic algorithms | number-theoretic algorithms | polynomial and matrix calculations | polynomial and matrix calculations | caching | caching | parallel computing | parallel computing

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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1.124J Foundations of Software Engineering (MIT) 1.124J Foundations of Software Engineering (MIT)

Description

This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J. This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J.

Subjects

modern software development | modern software development | engineering and information technology | engineering and information technology | component-based software | component-based software | C# | C# | .NET | .NET | data structures | data structures | algorithms for modeling | algorithms for modeling | analysis | analysis | visualization | visualization | basic problem-solving techniques | basic problem-solving techniques | web services | web services | management and maintenance of software | management and maintenance of software | sorting | sorting | searching | searching | algorithms | algorithms | numerical simulation techniques | numerical simulation techniques | image processing | image processing | computational geometry | computational geometry | finite element methods | finite element methods | network methods | network methods | e-business applications | e-business applications | classes | classes | objects | objects | inheritance | inheritance | virtual functions | virtual functions | abstract classes | abstract classes | polymorphism | polymorphism | Java applications | Java applications | applets | applets | Abstract Windowing Toolkit | Abstract Windowing Toolkit | Graphics | Graphics | Threads | Threads | Java | Java | C++ | C++ | information technology | information technology | engineering | engineering | modeling algorithms | modeling algorithms | basic problem-solving | basic problem-solving | software management | software management | software maintenance | software maintenance | searching algorithms | searching algorithms | numerical simulation | numerical simulation | object oriented programming | object oriented programming | 13.470J | 13.470J | 1.124 | 1.124 | 2.159 | 2.159 | 13.470 | 13.470

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.854J Advanced Algorithms (MIT) 6.854J Advanced Algorithms (MIT)

Description

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 programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures. 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 programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.

Subjects

amortization | amortization | randomization | randomization | fingerprinting | fingerprinting | word-level parallelism | word-level parallelism | bit scaling | bit scaling | dynamic programming | dynamic programming | network flow | network flow | linear programming | linear programming | fixed-parameter algorithms | fixed-parameter algorithms | approximation algorithms | approximation algorithms | string algorithms | string algorithms | network optimization | network optimization | parallel algorithms | parallel algorithms | computational geometry | computational geometry | online algorithms | online algorithms | external memory | external memory | external cache | external cache | external streaming | external streaming | data structures | data structures

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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18.319 Geometric Combinatorics (MIT) 18.319 Geometric Combinatorics (MIT)

Description

This course offers an introduction to discrete and computational geometry. Emphasis is placed on teaching methods in combinatorial geometry. Many results presented are recent, and include open (as yet unsolved) problems. This course offers an introduction to discrete and computational geometry. Emphasis is placed on teaching methods in combinatorial geometry. Many results presented are recent, and include open (as yet unsolved) problems.

Subjects

discrete geometry | discrete geometry | computational geometry | computational geometry | convex partitions | convex partitions | binary space partitions | binary space partitions | art gallery problems | art gallery problems | Planar graphs | Planar graphs | pseudo-triangulations | pseudo-triangulations | encompassing graphs | encompassing graphs | geometric graphs | geometric graphs | crossing numbers | crossing numbers | extremal graph theory | extremal graph theory | Gallai-Sylvester problems | Gallai-Sylvester problems

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.046J Introduction to Algorithms (SMA 5503) (MIT)

Description

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Subjects

algorithms | efficient algorithms | sorting | search trees | heaps | hashing | divide-and-conquer | dynamic programming | amortized analysis | graph algorithms | shortest paths | network flow | computational geometry | number-theoretic algorithms | polynomial and matrix calculations | caching | parallel computing

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.854J Advanced Algorithms (MIT)

Description

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 programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.

Subjects

amortization | randomization | fingerprinting | word-level parallelism | bit scaling | dynamic programming | network flow | linear programming | fixed-parameter algorithms | approximation algorithms | string algorithms | network optimization | parallel algorithms | computational geometry | online algorithms | external memory | external cache | external streaming | data structures

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.046J Introduction to Algorithms (SMA 5503) (MIT)

Description

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Subjects

algorithms | efficient algorithms | sorting | search trees | heaps | hashing | divide-and-conquer | dynamic programming | amortized analysis | graph algorithms | shortest paths | network flow | computational geometry | number-theoretic algorithms | polynomial and matrix calculations | caching | parallel computing | SMA 5503 | 6.046

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.854J Advanced Algorithms (MIT)

Description

6.854J is a first-year graduate course in algorithms, continuing where 6.046J left off. The course emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Topics include: data structures, network flows, linear programming, computational geometry, approximation algorithms.

Subjects

algorithm design and analysis | algorithms | fundamental algorithms | advanced methods of algorithmic design | analysis | implementation | data structures | network flows | linear programming | computational geometry | approximation algorithms | algorithmic design | algorithmic analysis | string algorithms | maximum flows | online algorithms | scheduling | external memory algorithms | 6.854 | 18.415

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.046J Introduction to Algorithms (MIT)

Description

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

Subjects

algorithms | efficient algorithms | sorting | search trees | heaps | hashing | divide-and-conquer | dynamic programming | amortized analysis | graph algorithms | shortest paths | network flow | computational geometry | number-theoretic algorithms | polynomial and matrix calculations | caching | parallel computing | 6.046 | 18.410

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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1.124J Foundations of Software Engineering (MIT)

Description

This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J.

Subjects

modern software development | engineering and information technology | component-based software | C# | .NET | data structures | algorithms for modeling | analysis | visualization | basic problem-solving techniques | web services | management and maintenance of software | sorting | searching | algorithms | numerical simulation techniques | image processing | computational geometry | finite element methods | network methods | e-business applications | classes | objects | inheritance | virtual functions | abstract classes | polymorphism | Java applications | applets | Abstract Windowing Toolkit | Graphics | Threads | Java | C++ | information technology | engineering | modeling algorithms | basic problem-solving | software management | software maintenance | searching algorithms | numerical simulation | object oriented programming | 13.470J | 1.124 | 2.159 | 13.470

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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18.319 Geometric Combinatorics (MIT)

Description

This course offers an introduction to discrete and computational geometry. Emphasis is placed on teaching methods in combinatorial geometry. Many results presented are recent, and include open (as yet unsolved) problems.

Subjects

discrete geometry | computational geometry | convex partitions | binary space partitions | art gallery problems | Planar graphs | pseudo-triangulations | encompassing graphs | geometric graphs | crossing numbers | extremal graph theory | Gallai-Sylvester problems

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.854J Advanced Algorithms (MIT)

Description

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 programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.

Subjects

amortization | randomization | fingerprinting | word-level parallelism | bit scaling | dynamic programming | network flow | linear programming | fixed-parameter algorithms | approximation algorithms | string algorithms | network optimization | parallel algorithms | computational geometry | online algorithms | external memory | external cache | external streaming | data structures

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.046J Introduction to Algorithms (SMA 5503) (MIT)

Description

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Subjects

algorithms | efficient algorithms | sorting | search trees | heaps | hashing | divide-and-conquer | dynamic programming | amortized analysis | graph algorithms | shortest paths | network flow | computational geometry | number-theoretic algorithms | polynomial and matrix calculations | caching | parallel computing

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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