124 citations · 206 across the 7 of their papers we have counts for
11 papers
Improving Online Algorithms via ML Predictions
Ravi Kumar, Manish Purohit, Zoya Svitkina
In this work we study the problem of using machine-learned predictions to improve the performance of online algorithms. We consider two classical problems, ski rental and non-clair…
New Tools for Peak Memory Scheduling
Ce Jin, Manish Purohit, Zoya Svitkina +2
We study scheduling of computation graphs to minimize peak memory consumption, an increasingly critical task due to the surge in popularity of large deep-learning models. This prob…
Efficient Caching with Reserves via Marking
Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina +2
Online caching is among the most fundamental and well-studied problems in the area of online algorithms. Innovative algorithmic ideas and analysis -- including potential functions…
Caching with Reserves
Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina +2
Caching is a crucial component of many computer systems, so naturally it is a well-studied topic in algorithm design. Much of traditional caching research studies cache management…
Scheduling with Communication Delay in Near-Linear Time
Quanquan C. Liu, Manish Purohit, Zoya Svitkina +2
We consider the problem of efficiently scheduling jobs with precedence constraints on a set of identical machines in the presence of a uniform communication delay. Such precedence-…
Scheduling Precedence-Constrained Jobs on Related Machines with Communication Delay
Biswaroop Maiti, Rajmohan Rajaraman, David Stalfa +2
We consider the problem of scheduling precedence-constrained jobs on uniformly-related machines in the presence of an arbitrary, fixed communication delay . We consider…