The field of optimization and quantum error correction is moving towards more efficient and accurate methods for computing complex problems. Researchers are focusing on developing new algorithms and techniques that can handle noisy functions, non-convex optimization problems, and high-dimensional data. One notable direction is the use of alternating minimization algorithms, which have been shown to be effective in computing quantum rate-distortion functions and other complex problems. Another area of interest is the development of new decoders for quantum error correction, which aim to reduce topological complexity and improve decoding times. Noteworthy papers include: Efficient Computation of Marton's Error Exponent via Constraint Decoupling, which proposes a composite maximization approach for computing the Marton's error exponent. SOME: Symmetric One-Hot Matching Elector, which introduces a novel decoder that reformulates the QEC decoding task as a Quadratic Unconstrained Binary Optimization problem.