Algorithm Design: Time Complexity Analysis

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Related lectures (22)

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Basic Ingredients of Algorithms

Covers the basic elements of algorithms, including data handling, instructions, and control structures.

Master Theorem: Time Complexity Analysis

Introduces the Master Theorem for analyzing algorithm time complexity through problem subdivision and formula application.

Solving Parity Games in Practice

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Processor Architecture

Covers processor architecture, evolution of performance, algorithms to computers transition, registers, instructions, arithmetic unit, and memory management.

Search Algorithms: Dichotomy Search

Explores dichotomy search algorithms, analyzing complexity and implementation details for efficient searching in sorted lists.

VLIW Architectures: Compilers and Instruction Level Parallelism

Covers VLIW architectures and compilers, focusing on instruction level parallelism and optimization techniques.

Introduction to Complexity

Introduces time complexity and worst-case analysis of algorithms, abstracting computational complexity from implementation details.

Introduction to Complexity

Introduces time complexity and worst-case analysis of algorithms, abstracting computational complexity from implementation details.

Proteins: Central Dogma and Translation

Explains protein synthesis, translation, and the central dogma of molecular biology.