Distributed processing of large-scale graph data has many practical applications and has
been widely studied. In recent years, a lot of distributed graph processing frameworks and …

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 …

We present a deterministic (1+ o (1))-approximation O (n 1/2+ o (1)+ D 1+ o (1))-time
algorithm for solving the single-source shortest paths problem on distributed weighted …

We give improved algorithms for the ℓp-regression problem, min x‖ x‖ p such that Ax= b,
for all p∊(1, 2)∪(2,∞). Our algorithms obtain a high accuracy solution in iterations, where …

This paper introduces the concept of low-congestion shortcuts for (near-) planar networks,
and demonstrates their power by using them to obtain near-optimal distributed algorithms for …

Many distributed optimization algorithms achieve existentially-optimal running times,
meaning that there exists some pathological worst-case topology on which no algorithm can …

We present a general framework of designing efficient dynamic approximate algorithms for
optimization problems on undirected graphs. In particular, we develop a technique that …

We devise new algorithms for the single-source shortest paths (SSSP) problem with non-
negative edge weights in the CONGEST model of distributed computing. While close-to …

We provide universally-optimal distributed graph algorithms for (1+∊)-approximate shortest
path problems including shortest-path-tree and transshipment. The universal optimality of …

In the distributed all-pairs shortest paths problem (APSP), every node in the weighted
undirected distributed network (the CONGEST model) needs to know the distance from …