Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization

8 November 2017

Papers citing "Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization"

12 / 12 papers shown

Title
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees Ally Yalei Du Eric Huang Dravyansh Sharma 56 0 0 18 Feb 2025
Learning-Based Heavy Hitters and Flow Frequency Estimation in Streams Rana Shahout Michael Mitzenmacher 25 2 0 24 Jun 2024
New Guarantees for Learning Revenue Maximizing Menus of Lotteries and Two-Part Tariffs Maria-Florina Balcan Hedyeh Beyhaghi 21 3 0 22 Feb 2023
Contextual Pandora's Box Alexia Atsidakou C. Caramanis Evangelia Gergatsouli O. Papadigenopoulos Christos Tzamos 23 5 0 26 May 2022
Triangle and Four Cycle Counting with Predictions in Graph Streams Justin Y. Chen T. Eden Piotr Indyk Honghao Lin Shyam Narayanan R. Rubinfeld Sandeep Silwal Tal Wagner David P. Woodruff Michael Zhang 38 20 0 17 Mar 2022
Learning Predictions for Algorithms with Predictions M. Khodak Maria-Florina Balcan Ameet Talwalkar Sergei Vassilvitskii 21 25 0 18 Feb 2022
Online Learning for Min Sum Set Cover and Pandora's Box Evangelia Gergatsouli Christos Tzamos 16 13 0 10 Feb 2022
Robustification of Online Graph Exploration Methods Franziska Eberle Alexander Lindermayr Nicole Megow L. Nolke Jens Schlöter AAML OOD 21 20 0 10 Dec 2021
Faster Matchings via Learned Duals M. Dinitz Sungjin Im Thomas Lavastida Benjamin Moseley Sergei Vassilvitskii 19 66 0 20 Jul 2021
Learnable and Instance-Robust Predictions for Online Matching, Flows and Load Balancing Thomas Lavastida Benjamin Moseley R. Ravi Chenyang Xu OOD 34 56 0 23 Nov 2020
Refined bounds for algorithm configuration: The knife-edge of dual class approximability Maria-Florina Balcan T. Sandholm Ellen Vitercik 6 14 0 21 Jun 2020
Smoothed Analysis of Online and Differentially Private Learning Nika Haghtalab Tim Roughgarden Abhishek Shetty 34 47 0 17 Jun 2020