Polar Coding for Binary Input Channels

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Explores simplifying belief propagation equations for pairwise models, reducing computational complexity from order n cubed to order n.

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

Explores countability and undecidable problems in the theory of computation.

Explores Projection Pursuit Regression for nonlinear modeling and the trade-offs with interpretability in neural networks.

Covers energy system modelling, optimization, scenarios, predictions, complexities, and controversies in energy models.

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

Explores algorithm complexity, time complexity estimation, Landau notations, and asymptotic behavior analysis.

Explores linear systems, direct methods, Gauss elimination, LU decomposition, and computational complexity.

Covers state space models and the expressivity of transformers in sequence copying tasks.