Explores causal inference, directed graphs, and fairness in algorithms, emphasizing conditional independence and the implications of DAGs.
Covers topics like DFS output, edge classification, acyclic graphs, correctness, time analysis, SCCs, and the Topological Sort algorithm.
Covers the concept of the exponential family and discusses forward and backward maps, expensive computations, parameters, functions, and convexity.
Covers the fundamentals of graph theory, including vertices, edges, degrees, walks, connected graphs, cycles, and trees, with a focus on the number of edges in a tree.
