Algorithms and Complexity
A tantárgyleírás hatályossága
| Subject name (Hungarian, English) |
Algoritmusok és bonyolultságuk
Algorithms and Complexity
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| Subject code | BMEVISZMA00 | ||||||||||||
| Subject type | — | ||||||||||||
| Training Level | — | ||||||||||||
| Course types and hours (weekly/semester) |
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| Assessment type | félévközi érdemjegy | ||||||||||||
| Credits | 4 | ||||||||||||
| Subject coordinator |
DR. Friedl Katalin
position: egyetemi docens
contact:
friedl.katalin@vik.bme.hu
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| Responsible department |
Számítástudományi és Információelméleti Tanszék
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| Faculty | Villamosmérnöki és Informatikai Kar | ||||||||||||
| Subject website | cs.bme.hu/algbony | ||||||||||||
| Primary curriculum type | — | ||||||||||||
| Direct prerequisites – Strong prerequisite | none | ||||||||||||
| Direct prerequisites – Weak prerequisite | none | ||||||||||||
| Direct prerequisites – Parallel prerequisite | none | ||||||||||||
| Direct prerequisites – Milestone prerequisite | none | ||||||||||||
| Direct prerequisites – Exclusion | none |
Objectives
Introduction of selected topics.
Interactive proofs -- a possible generalization of NP. Strong and weak players, the AM and IP classes. Probabilistically checkable proofs.
Communication complexity : computation with minimal information exchange. Connection to the matrix of the function. Nondeterministic complexity and its relation to deterministic complexity. Randomized protcols and their efficiency.
Geometrical algorithms: computations without division, closest pair of points, efficient convex hull computation .
Advanced search techniques: k-th element in linear time, computation of rank. How to store intervals
Pattern matching: KMP and Boyer-Moore algorithms. Pattern matching by finite automaton. Matching with errors, approximate solutions, and the efficient computation of edit distanc.
Parallel algorithms: variants of the PRAM model. Comparisons for simple cases. Computations organized in binary trees. The effect of changing the numer of processors (Brent's theorem)
Parallel algorithms for sorting (Batcher). Prefix sum computation and its applications. Computation of ranks.
Distributed algorithms: theoretical model. Leader selection algorithms on rings and on general graphs.
Distributed algorithms whith failers: fails in lines, when processors stop, and byzantine errors.
Network topologies from graph theoretical point of view: grid, cube, cube connected cycel, butterfly, Benes(shortest paths, diameter, cuts). Embeddings,algorithmical aspects.
Random graphs: different models, their basic properties (degrees, paths, connectedness). Random graphs as models of networks.
Parametric complexity: NP-hard problems with efficient solution for small values of a parameter. Bounding the depth of a search tree.Grpah minor theorem and consequences. The kernel method. W[1] complexity.
On-line algorithms: measure of effifiency. Examples. Scheduling algorithms.
Quantum computation: tools from linear algebra, simple algorithms (teleporting, Deusch-Jozsa). Qunatum Fourier transformation, the idea of prime factorization. Quantum cryptography.
Learning outcomes
Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:
Knowledge
No learning outcomes recorded.
Skills
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Attitudes
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Autonomy and responsibility
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Oktatási módszertan
Tanulástámogató anyagok
Online források
Recommended preliminary knowledge for completing the subject
General rules
Assessment methods
In-term assessments
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Weight of in-term assessments
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Exam-period assessments
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Weight of exam elements
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Grade calculation
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Attendance requirements
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Rules for retake and resubmission
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Short description
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Detailed description
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Recommended courses
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Workload to complete the subject
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