24 citations · 101 across the 38 of their papers we have counts for
11 papers · 1 filter
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
In this work, we study the problem of answering queries with -differential privacy, where each query has sensitivity one. We give an algorithm for this task that achiev…
Sample-efficient proper PAC learning with approximate differential privacy
Badih Ghazi, Noah Golowich, Ravi Kumar +1
In this paper we prove that the sample complexity of properly learning a class of Littlestone dimension with approximate differential privacy is , ignoring priva…
Robust and Private Learning of Halfspaces
Badih Ghazi, Ravi Kumar, Pasin Manurangsi +1
In this work, we study the trade-off between differential privacy and adversarial robustness under L2-perturbations in the context of learning halfspaces. We prove nearly tight bou…
Learning-Augmented Weighted Paging
Nikhil Bansal, Christian Coester, Ravi Kumar +2
We consider a natural semi-online model for weighted paging, where at any time the algorithm is given predictions, possibly with errors, about the next arrival of each page. The mo…
On Additive Approximate Submodularity
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar
A real-valued set function is (additively) approximately submodular if it satisfies the submodularity conditions with an additive error. Approximate submodularity arises in many se…
Online Linear Optimization with Many Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1
We study an online linear optimization (OLO) problem in which the learner is provided access to "hint" vectors in each round prior to making a decision. In this setting, we dev…