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MATHICSE Technical Report : On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Daniel Kressner, Stefano Massei, Alice Cortinovis

The problem of finding a

k\times k

submatrix of maximum volume of a matrix A is of interest in a variety of applications. For example, it yields a quasi-best low-rank approximation constructed from the rows and columns of A. We show that such a submatrix ...

MATHICSE2019

Laboratoire de systèmes adaptatifs

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Almost surely constrained convex optimization

Logit Pairing Methods Can Fool Gradient-Based Attacks

Learning Hawkes Processes from a Handful of Events

It is not either or: An initial investigation into combining collaborative and individual learning using an ITS

hm-toolbox: Matlab software for HODLR and HSS matrices

MATHICSE Technical Report : On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

On the Performance of Exact Diffusion over Adaptive Networks

Decentralized Decision-Making Over Multi-Task Networks

Discovery and Temporal Analysis of MOOC Study Patterns

Log Barriers for Safe Non-convex Black-box Optimization

Logit Pairing Methods Can Fool Gradient-Based Attacks

hm-toolbox: Matlab software for HODLR and HSS matrices

On the Performance of Exact Diffusion over Adaptive Networks

Discovery and Temporal Analysis of MOOC Study Patterns

MATHICSE Technical Report : On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Learning Hawkes Processes from a Handful of Events

It is not either or: An initial investigation into combining collaborative and individual learning using an ITS

Almost surely constrained convex optimization

Decentralized Decision-Making Over Multi-Task Networks

Log Barriers for Safe Non-convex Black-box Optimization