Mahshid Montazer Qaem

2 accepted papers

2021

Online Knapsack with Frequency Predictions

Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit

NeurIPS 2021poster

There has been recent interest in using machine-learned predictions to improve the worst-case guarantees of online algorithms. In this paper we continue this line of work by studying the online knapsack problem, but with very weak predictions: in the form of knowing an upper and lower bound for the…

Cited by 59 Source ↗PDF ↗Scholar ↗

2020

Fast Noise Removal for k-Means Clustering

Sungjin Im, Mahshid Montazer Qaem, Benjamin Moseley, Xiaorui Sun, Rudy Zhou

AISTATS 2020poster

This paper considers k-means clustering in the presence of noise. It is known that k-means clustering is highly sensitive to noise, and thus noise should be removed to obtain a quality solution. A popular formulation of this problem is called k-means clustering with outliers. The goal of k-means clu…

Cited by 37 Source ↗PDF ↗Scholar ↗