This article shows how to solve linear programs of the form min Ax = b , x ≥ 0 c ⊤ x with n variables in time O * (( n ω + n 2.5−α/2 + n 2+1/6 ) log ( n /δ)), where ω is the exponent of matrix multiplication, α is the dual exponent of matrix multiplication, and δ is the relative accuracy. For the current value of ω δ 2.37 and α δ 0.31, our algorithm takes O * ( n ω log ( n /δ)) time. When ω = 2, our algorithm takes O * ( n 2+1/6 log ( n /δ)) time. Our algorithm utilizes several new concepts that we believe may be of independent interest: • We define a stochastic central path method. • We show how to maintain a projection matrix √ W A ⊤ ( AWA ⊤ ) −1 A √ W in sub-quadratic time under 2 multiplicative changes in the diagonal matrix W .
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Cohen et al. (2021) studied this question.
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