Poster "approximation algorithms" Papers

24 papers found

Approximation algorithms for combinatorial optimization with predictions

Antonios Antoniadis, Marek Elias, Adam Polak et al.

ICLR 2025posterarXiv:2411.16600
3
citations

A Single-Swap Local Search Algorithm for k-Means of Lines

Ting Liang, Xiaoliang Wu, Junyu Huang et al.

NeurIPS 2025poster

A Unified Approach to Submodular Maximization Under Noise

Kshipra Bhawalkar, Yang Cai, Zhe Feng et al.

NeurIPS 2025posterarXiv:2510.21128

Efficient $k$-Sparse Band–Limited Interpolation with Improved Approximation Ratio

Yang Cao, Xiaoyu Li, Zhao Song et al.

NeurIPS 2025poster

Fair Clustering in the Sliding Window Model

Vincent Cohen-Addad, Shaofeng Jiang, Qiaoyuan Yang et al.

ICLR 2025posterarXiv:2503.05173
3
citations

Improved Algorithms for Fair Matroid Submodular Maximization

Sepideh Mahabadi, Sherry Sarkar, Jakub Tarnawski

NeurIPS 2025posterarXiv:2601.09860

Improved Approximation Algorithms for $k$-Submodular Maximization via Multilinear Extension

Huanjian Zhou, Lingxiao Huang, Baoxiang Wang

ICLR 2025poster

Learning-Augmented Streaming Algorithms for Correlation Clustering

Yinhao Dong, Shan Jiang, Shi Li et al.

NeurIPS 2025posterarXiv:2510.10705

Near-optimal Active Regression of Single-Index Models

Yi Li, Wai Ming Tai

ICLR 2025posterarXiv:2502.18213
1
citations

New Algorithms for the Learning-Augmented k-means Problem

Junyu Huang, Qilong Feng, Ziyun Huang et al.

ICLR 2025poster
1
citations

Provably Accurate Shapley Value Estimation via Leverage Score Sampling

Christopher Musco, R. Teal Witter

ICLR 2025posterarXiv:2410.01917
14
citations

Relax and Merge: A Simple Yet Effective Framework for Solving Fair $k$-Means and $k$-sparse Wasserstein Barycenter Problems

Shihong Song, Guanlin Mo, Hu Ding

ICLR 2025posterarXiv:2411.01115

Simple and Optimal Sublinear Algorithms for Mean Estimation

Beatrice Bertolotti, Matteo Russo, Chris Schwiegelshohn et al.

NeurIPS 2025posterarXiv:2406.05254

Stable Matching with Ties: Approximation Ratios and Learning

Shiyun Lin, Simon Mauras, Nadav Merlis et al.

NeurIPS 2025posterarXiv:2411.03270
2
citations

Streaming Algorithms For $\ell_p$ Flows and $\ell_p$ Regression

Amit Chakrabarti, Jeffrey Jiang, David Woodruff et al.

ICLR 2025poster

A Dynamic Algorithm for Weighted Submodular Cover Problem

Kiarash Banihashem, Samira Goudarzi, MohammadTaghi Hajiaghayi et al.

ICML 2024posterarXiv:2407.10003

A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering

Vincent Cohen-Addad, Tommaso d'Orsi, Aida Mousavifar

ICML 2024posterarXiv:2406.04857

Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS

Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani

ICML 2024posterarXiv:2406.07630

Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better

Vicente Balmaseda, Ying Xu, Yixin Cao et al.

ICML 2024posterarXiv:2404.16131

Consistent Submodular Maximization

PAUL DUETTING, Federico Fusco, Silvio Lattanzi et al.

ICML 2024poster

Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs

Slobodan Mitrovic, Theodore Pan

ICML 2024poster

Near-Linear Time Approximation Algorithms for k-means with Outliers

Junyu Huang, Qilong Feng, Ziyun Huang et al.

ICML 2024poster

Optimally Improving Cooperative Learning in a Social Setting

Shahrzad Haddadan, Cheng Xin, Jie Gao

ICML 2024posterarXiv:2405.20808

Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcal{NP}$-hard Problems

Evripidis Bampis, Bruno Escoffier, Michalis Xefteris

ICML 2024posterarXiv:2402.02062