Media Summary: Column Distribution & Thickness Optimization, Harvard GSD, 2016 Communication complexity (indexing, gap hamming) + application to median and F0 lower bounds. P-stable sketch analysis, Nisan's PRG, ℓp estimation for p larger than 2 via max-stability.

Column Distribution Thickness Optimization Harvard - Detailed Analysis & Overview

Column Distribution & Thickness Optimization, Harvard GSD, 2016 Communication complexity (indexing, gap hamming) + application to median and F0 lower bounds. P-stable sketch analysis, Nisan's PRG, ℓp estimation for p larger than 2 via max-stability. Simplex wrap-up, strong duality, complementary slackness, ellipsoid, intro to interior point. Path-following interior point, first order methods (gradient descent). Linear least squares via subspace embeddings, leverage score sampling, non-commutative Khintchine, oblivious subspace ...

Learning from experts, multiplicative weights. Randomized and approximate F0 lower bounds, disjointness, Fp lower bound, dimensionality reduction (JL lemma). Analysis of ℓp estimation algorithm via max-stability, deterministic point query via incoherent matrices. Online primal/dual: e/(e-1) ski rental, set cover; approximation algorithms via dual fitting: set cover.

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Column Distribution & Thickness Optimization, Harvard GSD, 2016
Algorithms for Big Data (COMPSCI 229r), Lecture 22
Algorithms for Big Data (COMPSCI 229r), Lecture 9
Algorithms for Big Data (COMPSCI 229r), Lecture 4
Advanced Algorithms (COMPSCI 224), Lecture 16
Advanced Algorithms (COMPSCI 224), Lecture 17
Algorithms for Big Data (COMPSCI 229r), Lecture 16
Algorithms for Big Data (COMPSCI 229r), Lecture 18
Advanced Algorithms (COMPSCI 224), Lecture 19
Algorithms for Big Data (COMPSCI 229r), Lecture 10
Algorithms for Big Data (COMPSCI 229r), Lecture 5
Advanced Algorithms (COMPSCI 224), Lecture 10
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Column Distribution & Thickness Optimization, Harvard GSD, 2016

Column Distribution & Thickness Optimization, Harvard GSD, 2016

Column Distribution & Thickness Optimization, Harvard GSD, 2016

Algorithms for Big Data (COMPSCI 229r), Lecture 22

Algorithms for Big Data (COMPSCI 229r), Lecture 22

Matrix completion.

Algorithms for Big Data (COMPSCI 229r), Lecture 9

Algorithms for Big Data (COMPSCI 229r), Lecture 9

Communication complexity (indexing, gap hamming) + application to median and F0 lower bounds.

Algorithms for Big Data (COMPSCI 229r), Lecture 4

Algorithms for Big Data (COMPSCI 229r), Lecture 4

P-stable sketch analysis, Nisan's PRG, ℓp estimation for p larger than 2 via max-stability.

Advanced Algorithms (COMPSCI 224), Lecture 16

Advanced Algorithms (COMPSCI 224), Lecture 16

Simplex wrap-up, strong duality, complementary slackness, ellipsoid, intro to interior point.

Advanced Algorithms (COMPSCI 224), Lecture 17

Advanced Algorithms (COMPSCI 224), Lecture 17

Path-following interior point, first order methods (gradient descent).

Algorithms for Big Data (COMPSCI 229r), Lecture 16

Algorithms for Big Data (COMPSCI 229r), Lecture 16

Linear least squares via subspace embeddings, leverage score sampling, non-commutative Khintchine, oblivious subspace ...

Algorithms for Big Data (COMPSCI 229r), Lecture 18

Algorithms for Big Data (COMPSCI 229r), Lecture 18

Low-rank approximation,

Advanced Algorithms (COMPSCI 224), Lecture 19

Advanced Algorithms (COMPSCI 224), Lecture 19

Learning from experts, multiplicative weights.

Algorithms for Big Data (COMPSCI 229r), Lecture 10

Algorithms for Big Data (COMPSCI 229r), Lecture 10

Randomized and approximate F0 lower bounds, disjointness, Fp lower bound, dimensionality reduction (JL lemma).

Algorithms for Big Data (COMPSCI 229r), Lecture 5

Algorithms for Big Data (COMPSCI 229r), Lecture 5

Analysis of ℓp estimation algorithm via max-stability, deterministic point query via incoherent matrices.

Advanced Algorithms (COMPSCI 224), Lecture 10

Advanced Algorithms (COMPSCI 224), Lecture 10

Online primal/dual: e/(e-1) ski rental, set cover; approximation algorithms via dual fitting: set cover.

Advanced Algorithms (COMPSCI 224), Lecture 13

Advanced Algorithms (COMPSCI 224), Lecture 13

Guest lecture: Rong Ge.