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Artistic Practices: Visual Timeline and Installations
Graph Chatbot
Related lectures (27)
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Graph Coloring: Theory and Applications
Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.
Elements of Computational Complexity
Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.
Complexity of Algorithms
Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.
The Local Hamiltonian Problem
Covers the Local Hamiltonian Problem, focusing on QMA-Complete problems and the complexity of verifying quantum computations.
Complexity of Algorithms: Big-O Notation
Explores algorithm complexity, big-O notation, induction, recursion, and analysis of running times, covering NP problems and complexity classes.
Theory of Computation: Decidability and Complexity
Delves into the theory of computation, covering decidability, complexity, P vs. NP, and reductions.
Support Vector Machines: Formulation and Complexity
Explores the formulation and complexity of Support Vector Machines, including primal and dual forms, geometric interpretation, and algorithmic implications.
Graph Coloring: Random vs Symmetrical
Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.
Implementation Strategies: Specifying and Operationalizing
Discusses a systematic approach for specifying and operationalizing implementation strategies.
