Category: Blog
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How to Learn ADMM: Variable Splitting, Augmented Lagrangians, Primal/Dual Residuals and Distributed Convex Optimization
A Learning Hall guide to ADMM, from variable splitting and augmented Lagrangians through proximal updates, primal/dual residuals, penalty tuning and distributed convex optimization.
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How to Learn FISTA: Proximal Operators, Momentum, Shrinkage, O(1/k²) Convergence and Restarted Sparse Optimization
A Learning Hall guide to FISTA, from proximal operators and ISTA through Nesterov acceleration, O(1/k²) convergence, backtracking, restart and professional sparse-optimization diagnostics.
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How to Learn the Leiden Algorithm: Local Moving, Refinement, Aggregation, CPM/Modularity and Well-Connected Communities
A Learning Hall guide to the Leiden algorithm, from Louvain failure modes and refinement through CPM/modularity, resolution, connectivity guarantees, randomness and professional community-detection validation.
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How to Learn the Lanczos Algorithm: Krylov Subspaces, Three-Term Recurrence, Ritz Values, Reorthogonalization and Sparse Eigenproblems
A Learning Hall guide to the Lanczos algorithm, from Krylov subspaces and the three-term recurrence through Ritz pairs, reorthogonalization, restarting, shift-invert and sparse eigenvalue engineering.
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How to Learn Reverse Cuthill–McKee: Sparse Matrix Reordering, Bandwidth Reduction, Pseudo-Peripheral Vertices and Solver Locality
A Learning Hall guide to Reverse Cuthill–McKee, from sparse matrices and graph bandwidth through degree-ordered BFS, pseudo-peripheral starts, permutations and professional solver benchmarking.
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How to Learn Welzl’s Algorithm: Smallest Enclosing Circles, Support Sets, Randomized Incremental Geometry and Expected Linear Time
A Learning Hall guide to Welzl’s randomized smallest-enclosing-circle algorithm, from support geometry and recursion through expected linear time, robustness and higher-dimensional generalization.
