2 citations · 2 across the 11 of their papers we have counts for
3 papers · 1 filter
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi +2
We design improved approximation algorithms for NP-hard graph problems by incorporating predictions (e.g., learned from past data). Our prediction model builds upon and extends the…
Optimal Algorithms for Augmented Testing of Discrete Distributions
Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld +1
We consider the problem of hypothesis testing for discrete distributions. In the standard model, where we have sample access to an underlying distribution , extensive research h…
Hardness and Algorithms for Robust and Sparse Optimization
Eric Price, Sandeep Silwal, Samson Zhou
We explore algorithms and limitations for sparse optimization problems such as sparse linear regression and robust linear regression. The goal of the sparse linear regression probl…