The Primal-Dual method for Learning Augmented Algorithms

22 October 2020

Papers citing "The Primal-Dual method for Learning Augmented Algorithms"

27 / 27 papers shown

Title
On Tradeoffs in Learning-Augmented Algorithms Ziyad Benomar Vianney Perchet 70 1 0 22 Jan 2025
Competitive Algorithms for Online Knapsack with Succinct Predictions Mohammadreza Daneshvaramoli Helia Karisani Adam Lechowicz Bo Sun Cameron Musco Mohammad Hajiesmaili 37 0 0 26 Jun 2024
Non-clairvoyant Scheduling with Partial Predictions Ziyad Benomar Vianney Perchet 48 6 0 02 May 2024
Learning-augmented Online Minimization of Age of Information and Transmission Costs Zhongdong Liu Keyuan Zhang Bin Li Yin Sun Y. T. Hou Bo Ji 36 3 0 05 Mar 2024
Learning-Based Algorithms for Graph Searching Problems A. DePavia Erasmo Tani A. Vakilian 48 2 0 27 Feb 2024
Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions Problems E. Kevi K. Nguyen 31 5 0 13 Feb 2024
Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions Tongxin Li Yiheng Lin Shaolei Ren Adam Wierman AAML OffRL 44 6 0 20 Jul 2023
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case Taihei Oki Shinsaku Sakaue 37 2 0 09 Jun 2023
Online Dynamic Acknowledgement with Learned Predictions Sungjin Im Benjamin Moseley Chenyang Xu Ruilong Zhang 18 4 0 25 May 2023
A Survey of Machine Learning-Based Ride-Hailing Planning Dacheng Wen Yupeng Li F. Lau 29 4 0 26 Mar 2023
Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis Yongho Shin Changyeol Lee Gukryeol Lee Hyung-Chan An 43 11 0 14 Feb 2023
Online Ad Allocation with Predictions Fabian Spaeh Alina Ene 27 1 0 03 Feb 2023
$Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster $\text{L}$-/$\text{L}^\natural$-Convex Function Minimization$ Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster $\text{L}$ -/ $\text{L}^\natural$ -Convex Function Minimization Shinsaku Sakaue Taihei Oki 41 2 0 02 Feb 2023
Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints Alexandra Lassota Alexander Lindermayr Nicole Megow Jens Schlöter 34 11 0 30 Jan 2023
Algorithms with Prediction Portfolios M. Dinitz Sungjin Im Thomas Lavastida Benjamin Moseley Sergei Vassilvitskii OOD 47 20 0 22 Oct 2022
Online TSP with Predictions Hsiao-Yu Hu Hao-Ting Wei Meng-Hsi Li Kai-Min Chung Chung-Shou Liao 26 3 0 30 Jun 2022
Contextual Pandora's Box Alexia Atsidakou Constantine Caramanis Evangelia Gergatsouli Orestis Papadigenopoulos Christos Tzamos 52 7 0 26 May 2022
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions Shinsaku Sakaue Taihei Oki 34 21 0 20 May 2022
A Regression Approach to Learning-Augmented Online Algorithms Keerti Anand Rong Ge Amit Kumar Debmalya Panigrahi 36 20 0 18 May 2022
Online Algorithms with Multiple Predictions Keerti Anand Rong Ge Ajay Kumar Debmalya Panigrahi 32 34 0 08 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 80 21 0 17 Mar 2022
Permutation Predictions for Non-Clairvoyant Scheduling Alexander Lindermayr Nicole Megow 37 31 0 21 Feb 2022
Learning Predictions for Algorithms with Predictions M. Khodak Maria-Florina Balcan Ameet Talwalkar Sergei Vassilvitskii 48 25 0 18 Feb 2022
Parsimonious Learning-Augmented Caching Sungjin Im Ravi Kumar Aditya Petety Manish Purohit 58 27 0 09 Feb 2022
Learning-Augmented Algorithms for Online Steiner Tree Chenyang Xu Benjamin Moseley 33 17 0 10 Dec 2021
Faster Matchings via Learned Duals M. Dinitz Sungjin Im Thomas Lavastida Benjamin Moseley Sergei Vassilvitskii 24 67 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 42 57 0 23 Nov 2020