Introduction to Algorithms For Big Data Compsci 229r Lecture 23
Exploring Algorithms For Big Data Compsci 229r Lecture 23 reveals several interesting facts. External memory model: linked list, matrix multiplication, B-tree, buffered repository tree, sorting.
Algorithms For Big Data Compsci 229r Lecture 23 Comprehensive Overview
Competitive paging, cache-oblivious MapReduce: TeraSort, minimum spanning tree, triangle counting. Path-following interior point, first order methods (gradient descent).
Heavy
Summary & Highlights for Algorithms For Big Data Compsci 229r Lecture 23
- Matrix completion.
- second order methods (Newton's method), path-following interior point wrap-up.
- Amnesic dynamic programming (approximate distance to monotonicity).
- Power of random signs: ℓ2 norm estimation, subspace embeddings (regression), Johnson-Lindenstrauss, deterministic point ...
- Logistics, course topics, basic tail bounds (Markov, Chebyshev, Chernoff, Bernstein), Morris'
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