2 citations · 3 across the 4 of their papers we have counts for
4 papers
Online Scheduling via Gradient Descent for Weighted Flow Time Minimization
Qingyun Chen, Sungjin Im, Aditya Petety
In this paper, we explore how a natural generalization of Shortest Remaining Processing Time (SRPT) can be a powerful \emph{meta-algorithm} for online scheduling. The meta-algorith…
Online Load and Graph Balancing for Random Order Inputs
Sungjin Im, Ravi Kumar, Shi Li +2
Online load balancing for heterogeneous machines aims to minimize the makespan (maximum machine workload) by scheduling arriving jobs with varying sizes on different machines. In t…
Parsimonious Learning-Augmented Caching
Sungjin Im, Ravi Kumar, Aditya Petety +1
Learning-augmented algorithms -- in which, traditional algorithms are augmented with machine-learned predictions -- have emerged as a framework to go beyond worst-case analysis. Th…
Attribute noise robust binary classification
Aditya Petety, Sandhya Tripathi, N Hemachandra
We consider the problem of learning linear classifiers when both features and labels are binary. In addition, the features are noisy, i.e., they could be flipped with an unknown pr…