Complexity class

Related lectures (30)

Page 3 of 3

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Explores algorithmic challenges, time complexity, optimization, recursion, and probability calculations.

Delves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.

Covers counting distinct elements using hash functions and the median trick.

Covers the time complexity of algorithms and includes a quiz.

Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.

Covers complexity classes, tractable problems, the class NP, NP-complete problems, and summarizes the concept of tractable problems.

Explores the Bias-Variance tradeoff in machine learning, emphasizing the balance between bias and variance in model predictions.

Covers complexity classes, effect on computer time, tractable problems, class NP, and NP-complete problems.

Explores the connection between spin glasses and holography, focusing on disorder, the SYK model, and the quantum butterfly effect.