Publications associées à Matrix Implementations

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New Results in Integer and Lattice Programming

Christoph Hunkenschröder

An integer program (IP) is a problem of the form

\min \{f(x) : \, Ax = b, \ l \leq x \leq u, \ x \in \Z^n\}

, where

A \in \Z^{m \times n}

b \in \Z^m

l,u \in \Z^n

, and

f: \Z^n \rightarrow \Z

is a separable convex objective function. The problem o ...

EPFL2020

Matrix Implementations

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COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Preconditioning techniques for generalized Sylvester matrix equations

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

On the fast assemblage of finite element matrices with application to nonlinear heat transfer problems

Fast deterministic and randomized algorithms for low-rank approximation, matrix functions, and trace estimation

DIVIDE-AND-CONQUER METHODS FOR FUNCTIONS OF MATRICES WITH BANDED OR HIERARCHICAL LOW-RANK STRUCTURE\ast

Harmonic decomposition of the trace of 1D transfer matrices in layered media

Faster Monotone Min-Plus Product, Range Mode, and Single Source Replacement Paths

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

New Results in Integer and Lattice Programming

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Preconditioning techniques for generalized Sylvester matrix equations

Harmonic decomposition of the trace of 1D transfer matrices in layered media

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

On the fast assemblage of finite element matrices with application to nonlinear heat transfer problems

DIVIDE-AND-CONQUER METHODS FOR FUNCTIONS OF MATRICES WITH BANDED OR HIERARCHICAL LOW-RANK STRUCTURE\ast

New Results in Integer and Lattice Programming

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Fast deterministic and randomized algorithms for low-rank approximation, matrix functions, and trace estimation

Faster Monotone Min-Plus Product, Range Mode, and Single Source Replacement Paths