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DAVE ANDERSON

MATHEMATICS PHD PROGRAM, UC BERKELEY


I am a final year PhD student at UC Berkeley researching low-rank data approximation algorithms. My areas of specialization include randomized algorithms, communication-avoiding algorithms, rank-revealing algorithms, and numeric linear algebra.

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Papers



An Efficient, Sparsity-Preserving, Online Algorithm for Data Approximation

David G. Anderson and Ming Gu

Under review, arxiv.org/abs/1602.05950, 2016


Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nystrom Method

David G. Anderson, Simon Du, Ming Gu, Michael Mahoney, Christopher Melgaard, and Kunming Wu

AISTATS, http://jmlr.org/proceedings/papers/v38/anderson15.pdf, 2015


An Efficient Algorithm for Unweighted Spectral Graph Sparsification

David G. Anderson, Ming Gu, and Christopher Melgaard

Under review, arXiv/abs/1410.4273, 2015


Improved Algorithms for Column-Based Matrix Reconstruction

David G. Anderson, Simon Du, Ming Gu, Christopher Melgaard, and Kunming Wu

2014

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Teaching



Fall 2014 : Math 375sample

Spring 2014 : Math 128A

Fall 2013 : Math 228A

Fall 2012 : Math 16B

Spring 2012 : Math 16A

Fall 2011 : Math 32

Spring 2011 : Math 1B

 


CV GitHub