Implement Sparse Matrix Operations

Implement core sparse linear-algebra utilities for interview-style ML code. Tasks: 1. Compute the dot product of two sparse vectors efficiently. 2. Implement multiplication of two sparse matrices efficiently. 3. Compare coordinate-list and compressed-sparse-row style representations for these operations, and explain the trade-offs in memory usage and runtime. You may assume sparse vectors are represented by sorted `(index, value)` pairs, and sparse matrices are represented either as nonzero triples `(row, col, value)` or an equivalent compressed sparse structure.