Lectures related to Promise Constraint Satisfaction and Width

Covers optimization algorithms, convergence properties, and time complexity of sequences and functions.

Explores countability and undecidable problems in the theory of computation.

Covers the formulation of constraint satisfaction problems and systematic algorithms for solving them efficiently.

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Covers challenges in bit-precise reasoning, including SMT-COMP results, AIG, bit-blasting, Tseitin transformation, and complexity classes.

Covers the complexity analyses of algorithms and their worst-case time complexities.

Introduces the backpack problem, a discrete optimization problem with constraints and algorithms to solve it.