Lecture

Dynamic Programming: Introduction and Fibonacci Numbers

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In course

CS-250: Algorithms I

The students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, major algorithmic paradigms such as dynamic programming, s ...

Description

This lecture introduces Dynamic Programming as an algorithmic paradigm, focusing on the main idea of saving computation by remembering previous calculations. It covers the application of Dynamic Programming to solve optimization problems, with a specific example of calculating Fibonacci numbers efficiently. The lecture also discusses the top-down approach with memoization and its benefits in optimizing recursive algorithms. The content progresses to explain the process of cutting a rod to maximize profit using Dynamic Programming. The lecture concludes by highlighting the exponential inefficiency of a naive recursive approach.

Instructors (3)

Mikhail Kapralov

Teaching & PhD PhD Students Weronika Wrzos-Kaminska, Guy Weissenberg, Davide Mazzali, Ekaterina Kochetkova, Kshiteej Jitesh Sheth Past EPFL PhD Students Amir Zandieh, Aidasadat Mousavifar, Navid Nouri, Jakab Tardos, Grzegorz Adam Gluch, Makarov Mikhail Past EPFL PhD Students as codirector Paritosh Garg Courses Algorithms II CS-450 The students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing alg

Ola Nils Anders Svensson

Alessandro Chiesa

Alessandro Chiesa is a faculty member in computer science. He conducts research in complexity theory, cryptography, and security, with a focus on the theoretical foundations and practical implementations of cryptographic proofs that are short and easy to verify. He is a co-author of several zkSNARK libraries, and is a co-inventor of the Zerocash protocol. He has co-founded Zcash and StarkWare Industries. He is a recipient of a Sloan Research Fellowship (2021), an Okawa Foundation Research Grant (2020), and Google Faculty Research Awards (2018 and 2017). He was included in MIT Technology Review's "35 Innovators Under 35" list in 2018.

Official source

Related concepts (30)

Fibonacci sequence

In mathematics, the Fibonacci sequence is a sequence in which each number is the sum of the two preceding ones. Numbers that are part of the Fibonacci sequence are known as Fibonacci numbers, commonly denoted Fn . The sequence commonly starts from 0 and 1, although some authors start the sequence from 1 and 1 or sometimes (as did Fibonacci) from 1 and 2. Starting from 0 and 1, the first few values in the sequence are: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144.

Generalizations of Fibonacci numbers

In mathematics, the Fibonacci numbers form a sequence defined recursively by: That is, after two starting values, each number is the sum of the two preceding numbers. The Fibonacci sequence has been studied extensively and generalized in many ways, for example, by starting with other numbers than 0 and 1, by adding more than two numbers to generate the next number, or by adding objects other than numbers. Using , one can extend the Fibonacci numbers to negative integers. So we get: −8, 5, −3, 2, −1, 1, 0, 1, 1, 2, 3, 5, 8, .

Program optimization

In computer science, program optimization, code optimization, or software optimization, is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. In general, a computer program may be optimized so that it executes more rapidly, or to make it capable of operating with less memory storage or other resources, or draw less power. Although the word "optimization" shares the same root as "optimal", it is rare for the process of optimization to produce a truly optimal system.

Fibonacci coding

In mathematics and computing, Fibonacci coding is a universal code which encodes positive integers into binary code words. It is one example of representations of integers based on Fibonacci numbers. Each code word ends with "11" and contains no other instances of "11" before the end. The Fibonacci code is closely related to the Zeckendorf representation, a positional numeral system that uses Zeckendorf's theorem and has the property that no number has a representation with consecutive 1s.

Dynamic programming

Dynamic programming is both a mathematical optimization method and an algorithmic paradigm. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics. In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively.

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Recursive Functions: Examples and Applications

Explores recursive functions, including factorials and Fibonacci sequences, and their scope and namespaces.

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