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Related lectures (32)

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Graph Coloring and Directed Cycles

Explores graph coloring, directed cycles, LLL algorithm applications, and element dependencies in graphs.

Dynamic Programming: Fibonacci Numbers

Explores dynamic programming with Fibonacci numbers, greedy coin change algorithms, graph coloring, and knapsack variants.

Graph Coloring: Theory and Applications

Explores graph coloring theory, spectral clustering, community detection, and network structures.

Covers register allocation techniques, including interference graph examples, coloring, spilling, and coalescing.

Markov Chains and Algorithm Applications

Covers the application of Markov chains and algorithms for function optimization and graph colorings.

Statistical Physics for Optimization & Learning

Covers statistical physics tools for optimization, learning, graph coloring, recommendation systems, and neural networks.

Optimization: Register Allocation

Covers advanced compiler construction topics on optimization techniques like dead code elimination, constant folding, and register allocation.

Algorithmic Paradigms for Dynamic Graph Problems

Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.

Minimum Spanning Trees: Prim's Algorithm

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Linear Algebra: Matrix Representation

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.