124 citations · 125 across the 4 of their papers we have counts for
4 papers
Adaptive Weighted Averaging
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1
We study the problem of selecting the largest among unknown values given only a single unbiased estimate for each . We design strategies that are sim…
On the Randomized Locality of Matching Problems in Regular Graphs
Seri Khoury, Manish Purohit, Aaron Schild +1
The main goal in distributed symmetry-breaking is to understand the locality of problems; i.e., the radius of the neighborhood that a node needs to explore in order to arrive at it…
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…