Maximum flow and minimum-cost flow in almost-linear time
We give an algorithm that computes exact maximum flows and minimum-cost flows on
directed graphs with m edges and polynomially bounded integral demands, costs, and …
directed graphs with m edges and polynomially bounded integral demands, costs, and …
A deterministic almost-linear time algorithm for minimum-cost flow
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 …
minimum-cost flows on directed graphs with m edges and polynomially bounded integral …
A survey on exact algorithms for the maximum flow and minimum‐cost flow problems
O Cruz‐Mejía, AN Letchford - Networks, 2023 - Wiley Online Library
Network flow problems form an important and much‐studied family of combinatorial
optimization problems, with a huge array of practical applications. Two network flow …
optimization problems, with a huge array of practical applications. Two network flow …
Fully dynamic electrical flows: Sparse maxflow faster than Goldberg–Rao
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 …
capacities in the range in time. We use to suppress logarithmic factors in. For sparse graphs …
Mongoose: A learnable lsh framework for efficient neural network training
Recent advances by practitioners in the deep learning community have breathed new life
into Locality Sensitive Hashing (LSH), using it to reduce memory and time bottlenecks in …
into Locality Sensitive Hashing (LSH), using it to reduce memory and time bottlenecks in …
A faster algorithm for solving general lps
The fastest known LP solver for general (dense) linear programs is due to [Cohen, Lee and
Song'19] and runs in O*(n ω+ n 2.5− α/2+ n 2+ 1/6) time. A number of follow-up works [Lee …
Song'19] and runs in O*(n ω+ n 2.5− α/2+ n 2+ 1/6) time. A number of follow-up works [Lee …
Unit Capacity Maxflow in Almost Time
We present an algorithm which given any m-edge directed graph with positive integer
capacities at most U, vertices a and b, and an approximation parameter ϵ∈(0,1) computes …
capacities at most U, vertices a and b, and an approximation parameter ϵ∈(0,1) computes …
Mitigating manipulation in peer review via randomized reviewer assignments
We consider three important challenges in conference peer review:(i) reviewers maliciously
attempting to get assigned to certain papers to provide positive reviews, possibly as part of …
attempting to get assigned to certain papers to provide positive reviews, possibly as part of …
Deterministic decremental sssp and approximate min-cost flow in almost-linear time
A Bernstein, MP Gutenberg… - 2021 IEEE 62nd Annual …, 2022 - ieeexplore.ieee.org
In the decremental single-source shortest paths problem, the goal is to maintain distances
from a fixed source s to every vertex v in an m-edge graph undergoing edge deletions. In …
from a fixed source s to every vertex v in an m-edge graph undergoing edge deletions. In …
Breaking the linear iteration cost barrier for some well-known conditional gradient methods using maxip data-structures
Conditional gradient methods (CGM) are widely used in modern machine learning. CGM's
overall running time usually consists of two parts: the number of iterations and the cost of …
overall running time usually consists of two parts: the number of iterations and the cost of …