Main Takeaway: Power of random signs: ℓ2 norm estimation, subspace embeddings (regression), Johnson-Lindenstrauss, deterministic point ... Linear least squares via subspace embeddings, leverage score sampling, non-commutative Khintchine, oblivious subspace ...
Advanced Algorithms Compsci 224 Lecture 16 -
Power of random signs: ℓ2 norm estimation, subspace embeddings (regression), Johnson-Lindenstrauss, deterministic point ... Linear least squares via subspace embeddings, leverage score sampling, non-commutative Khintchine, oblivious subspace ... Symmetrization, hashing: linear probing (5-wise indep.), bloom filters, cuckoo hashing, bloomier filters.
Important details found
- Power of random signs: ℓ2 norm estimation, subspace embeddings (regression), Johnson-Lindenstrauss, deterministic point ...
- Linear least squares via subspace embeddings, leverage score sampling, non-commutative Khintchine, oblivious subspace ...
- Symmetrization, hashing: linear probing (5-wise indep.), bloom filters, cuckoo hashing, bloomier filters.
- Simplex wrap-up, strong duality, complementary slackness, ellipsoid, intro to interior point.
- Loeb Associate Professor of Engineering and Applied Sciences at the Harvard John A.
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