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Free 229R courses, lessons, transcripts, and guided learning paths on CourseHive.
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MapReduce: TeraSort, minimum spanning tree, triangle counting.
Algorithms for Big Data (COMPSCI 229r)Competitive paging, cache-oblivious algorithms: matrix multiplication, self-organizing linked list, static B-tree, lazy funnelsort.
Algorithms for Big Data (COMPSCI 229r)External memory model: linked list, matrix multiplication, B-tree, buffered repository tree, sorting.
Algorithms for Big Data (COMPSCI 229r)Matrix completion.
Algorithms for Big Data (COMPSCI 229r)ℓ1/ℓ1 recovery, RIP1, unbalanced expanders, Sequential Sparse Matching Pursuit.
Algorithms for Big Data (COMPSCI 229r)Krahmer-Ward proof, Iterative Hard Thresholding.
Algorithms for Big Data (COMPSCI 229r)RIP and connection to incoherence, basis pursuit, Krahmer-Ward theorem.
Algorithms for Big Data (COMPSCI 229r)Low-rank approximation, column-based matrix reconstruction, k-means, compressed sensing.
Algorithms for Big Data (COMPSCI 229r)Oblivious subspace embeddings, faster iterative regression, sketch-and-solve regression.
Algorithms for Big Data (COMPSCI 229r)Linear least squares via subspace embeddings, leverage score sampling, non-commutative Khintchine, oblivious subspace embeddings.
Algorithms for Big Data (COMPSCI 229r)Approximate matrix multiplication with Frobenius error via sampling / JL, matrix median trick, subspace embeddings.
Algorithms for Big Data (COMPSCI 229r)Sparse JL proof wrap-up, Fast JL Transform, approximate nearest neighbor.
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