We give a deterministic m^1+o(1) time algorithm that computes exact maximum flows and
minimum-cost flows on directed graphs with m edges and polynomially bounded integral …

Privacy-preserving online multi-task assignment is a crucial aspect of spatial crowdsensing
on untrusted platforms, where multiple real-time tasks are allocated to appropriate workers …

Network flow problems form an important and much‐studied family of combinatorial
optimization problems, with a huge array of practical applications. Two network flow …

We give an algorithm for computing exact maximum flows on graphs with edges and integer
capacities in the range in time. We use to suppress logarithmic factors in. For sparse graphs …

Vizing's celebrated theorem states that every simple graph with maximum degree Δ admits a
(Δ+ 1) edge coloring which can be found in O (m· n) time on n-vertex m-edge graphs. This is …

We present a randomized algorithm that computes single-source shortest paths (SSSP) in
O\left(m\log^8(n)\logW\right) time when edge weights are integral and can be negative. 1 …

The-norm regression problem is a classic problem in optimization with wide ranging
applications in machine learning and theoretical computer science. The goal is to compute …

We give a deterministic (global) min-cut algorithm for weighted undirected graphs that runs
in time O (m 1+ ε) plus polylog (n) max-flow computations. Using the current best max-flow …

In 1961, Gomory and Hu showed that the All-Pairs Max-Flow problem of computing the max-
flow between all n\2 pairs of vertices in an undirected graph can be solved using only n-1 …

Augmenting algorithms with learned predictions is a promising approach for going beyond
worst-case bounds. Dinitz, Im, Lavastida, Moseley, and Vassilvitskii~(2021) have …