Understanding Advanced Algorithms Lecture 13 Fall 2016

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Key Takeaways about Advanced Algorithms Lecture 13 Fall 2016

  • Instructor : Aditya Bhaskara Formalizing flows, Max flow, Greedy routing, Ford-Fulkerson
  • Online primal/dual: e/(e-1) ski rental, set cover; approximation
  • Power of random signs: ℓ2 norm estimation, subspace embeddings (regression), Johnson-Lindenstrauss, deterministic point ...
  • More efficient exponential-time
  • Amortized analysis, binomial heaps, Fibonacci heaps.

Detailed Analysis of Advanced Algorithms Lecture 13 Fall 2016

Guest My Event Description. Hashing: load balancing, k-wise independence, chaining, linear probing.

Lecture 13

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