Prize-Collecting Survivable Network Design in Node-Weighted Graphs. - Chandra Chekuri; Alina Ene; Ali Vakilian (APPROX-RANDOM, 2012)

Improved Approximation Algorithms for Connected Domatic Partitions and Related Problems - Alina Ene; Nitish Korula; Ali Vakilian (CoRR, 2013)

Which concepts are worth extracting? - Arash Termehchy; Ali Vakilian; Yodsawalai Chodpathumwan; Marianne Winslett (SIGMOD Conference, 2014)

Improved approximation algorithms for degree-bounded network design problems with node connectivity requirements. - Alina Ene; Ali Vakilian (STOC, 2014)

On Streaming and Communication Complexity of the Set Cover Problem. - Erik D. Demaine; Piotr Indyk; Sepideh Mahabadi; Ali Vakilian (DISC, 2014)

Towards Tight Bounds for the Streaming Set Cover Problem. - Piotr Indyk; Sepideh Mahabadi; Ali Vakilian (CoRR, 2015)

Cost-Effective Conceptual Design for Information Extraction. - Arash Termehchy; Ali Vakilian; Yodsawalai Chodpathumwan; Marianne Winslett (ACM Trans. Database Syst., 2015)

Towards Tight Bounds for the Streaming Set Cover Problem. - Sariel Har-Peled; Piotr Indyk; Sepideh Mahabadi; Ali Vakilian (PODS, 2016)

Fractional Set Cover in the Streaming Model. - Piotr Indyk; Sepideh Mahabadi; Ronitt Rubinfeld; Jonathan R. Ullman; Ali Vakilian; Anak Yodpinyanee (APPROX-RANDOM, 2017)

Cost-Effective Conceptual Design Over Taxonomies. - Ali Vakilian; Yodsawalai Chodpathumwan; Arash Termehchy; Amir Nayyeri (WebDB, 2017)

Set Cover in Sub-linear Time. - Piotr Indyk; Sepideh Mahabadi; Ronitt Rubinfeld; Ali Vakilian; Anak Yodpinyanee (SODA, 2018)

Cost-effective conceptual design using taxonomies. - Yodsawalai Chodpathumwan; Ali Vakilian; Arash Termehchy; Amir Nayyeri (VLDB J., 2018)

Sample-Optimal Low-Rank Approximation of Distance Matrices. - Piotr Indyk; Ali Vakilian; Tal Wagner; David P. Woodruff (COLT, 2019)

Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. - Erik D. Demaine; Timothy D. Goodrich; Kyle Kloster; Brian Lavallee; Quanquan C. Liu; Blair D. Sullivan; Ali Vakilian; Andrew van der Poel (ESA, 2019)

Learning-Based Frequency Estimation Algorithms. - Chen-Yu Hsu 001; Piotr Indyk; Dina Katabi; Ali Vakilian (ICLR (Poster), 2019)

Scalable Fair Clustering. - Arturs Backurs; Piotr Indyk; Krzysztof Onak; Baruch Schieber; Ali Vakilian; Tal Wagner (ICML, 2019)

Local Computation Algorithms for Spanners. - Merav Parter; Ronitt Rubinfeld; Ali Vakilian; Anak Yodpinyanee (ITCS, 2019)

Learning-Based Low-Rank Approximations. - Piotr Indyk; Ali Vakilian; Yang Yuan (NeurIPS, 2019)

Tight Trade-offs for the Maximum k-Coverage Problem in the General Streaming Model. - Piotr Indyk; Ali Vakilian (PODS, 2019)

(Learned) Frequency Estimation Algorithms under Zipfian Distribution. - Anders Aamand; Piotr Indyk; Ali Vakilian (CoRR, 2019)

Individual Fairness for k-Clustering. - Sepideh Mahabadi; Ali Vakilian (ICML, 2020)

Improved Local Computation Algorithm for Set Cover via Sparsification. - Christoph Grunau; Slobodan Mitrovic; Ronitt Rubinfeld; Ali Vakilian (SODA, 2020)

On Learned Sketches for Randomized Numerical Linear Algebra. - Simin Liu; Tianrui Liu; Ali Vakilian; Yulin Wan; David P. Woodruff (CoRR, 2020)

Approximation Algorithms for Socially Fair Clustering. - Yury Makarychev; Ali Vakilian (COLT, 2021)

Learning Online Algorithms with Distributional Advice. - Ilias Diakonikolas; Vasilis Kontonis; Christos Tzamos; Ali Vakilian; Nikos Zarifis (ICML, 2021)

Node-weighted Network Design in Planar and Minor-closed Families of Graphs. - Chandra Chekuri; Alina Ene; Ali Vakilian (ACM Trans. Algorithms, 2021)

Improved Approximation Algorithms for Individually Fair Clustering. - Ali Vakilian; Mustafa Yalçiner (AISTATS, 2022)

Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. - Avrim Blum; Kevin Stangl; Ali Vakilian (FAccT, 2022)

Fair Representation Clustering with Several Protected Classes. - Zhen Dai; Yury Makarychev; Ali Vakilian (FAccT, 2022)

Individual Preference Stability for Clustering. - Saba Ahmadi; Pranjal Awasthi; Samir Khuller; Matthäus Kleindessner; Jamie Morgenstern; Pattara Sukprasert; Ali Vakilian (ICML, 2022)

Faster Fundamental Graph Algorithms via Learned Predictions. - Justin Y. Chen; Sandeep Silwal; Ali Vakilian; Fred Zhang (ICML, 2022)

Approximating Fair Clustering with Cascaded Norm Objectives. - Eden Chlamtác; Yury Makarychev; Ali Vakilian (SODA, 2022)

Approximating Red-Blue Set Cover and Minimum Monotone Satisfying Assignment. - Eden Chlamtác; Yury Makarychev; Ali Vakilian (APPROX/RANDOM, 2023)

Learning the Positions in CountSketch. - Yi Li 002; Honghao Lin; Simin Liu; Ali Vakilian; David P. Woodruff (ICLR, 2023)

Sequential Strategic Screening. - Lee Cohen 001; Saeed Sharifi-Malvajerdi; Kevin Stangl; Ali Vakilian; Juba Ziani (ICML, 2023)

Approximation Algorithms for Fair Range Clustering. - Sèdjro Salomon Hotegni; Sepideh Mahabadi; Ali Vakilian (ICML, 2023)

Constant Approximation for Individual Preference Stable Clustering. - Anders Aamand; Justin Y. Chen; Allen Liu; Sandeep Silwal; Pattara Sukprasert; Ali Vakilian; Fred Zhang (NeurIPS, 2023)

Improved Frequency Estimation Algorithms with and without Predictions. - Anders Aamand; Justin Y. Chen; Huy Lê Nguyen; Sandeep Silwal; Ali Vakilian (NeurIPS, 2023)

Tight Bounds for Volumetric Spanners and Applications. - Aditya Bhaskara; Sepideh Mahabadi; Ali Vakilian (NeurIPS, 2023)

Approximating Red-Blue Set Cover. - Eden Chlamtác; Yury Makarychev; Ali Vakilian (CoRR, 2023)

Learning-Based Algorithms for Graph Searching Problems. - Adela Frances DePavia; Erasmo Tani; Ali Vakilian (AISTATS, 2024)

Scalable Algorithms for Individual Preference Stable Clustering. - Ron Mosenzon; Ali Vakilian (AISTATS, 2024)

Streaming Algorithms for Connectivity Augmentation. - Ce Jin 001; Michael Kapralov; Sepideh Mahabadi; Ali Vakilian (ICALP, 2024)

Bayesian Strategic Classification. - Lee Cohen 001; Saeed Sharifi-Malvajerdi; Kevin Stangl; Ali Vakilian; Juba Ziani (NeurIPS, 2024)

On Socially Fair Low-Rank Approximation and Column Subset Selection. - Zhao Song 002; Ali Vakilian; David P. Woodruff; Samson Zhou (NeurIPS, 2024)

A Polynomial-Time Approximation for Pairwise Fair k-Median Clustering. - Sayan Bandyapadhyay; Eden Chlamtác; Yury Makarychev; Ali Vakilian (CoRR, 2024)

Streaming Algorithms for Network Design. - Chandra Chekuri; Rhea Jain; Sepideh Mahabadi; Ali Vakilian (APPROX/RANDOM, 2025)

Max-Cut with Multiple Cardinality Constraints. - Yury Makarychev; Madhusudhan Reddy Pittu; Ali Vakilian (APPROX/RANDOM, 2025)

Guessing Efficiently for Constrained Subspace Approximation. - Aditya Bhaskara; Sepideh Mahabadi; Madhusudhan Reddy Pittu; Ali Vakilian; David P. Woodruff (ICALP, 2025)

New and Improved Bounds for Markov Paging. - Chirag Pabbaraju; Ali Vakilian (ICALP, 2025)

Learning-Augmented Streaming Algorithms for Approximating MAX-CUT. - Yinhao Dong; Pan Peng 001; Ali Vakilian (ITCS, 2025)

Sublinear Metric Steiner Tree via Improved Bounds for Set Cover. - Sepideh Mahabadi; Mohammad Roghani; Jakub Tarnawski; Ali Vakilian (ITCS, 2025)

Minimax Group Fairness in Strategic Classification. - Emily Diana; Saeed Sharifi-Malvajerdi; Ali Vakilian (SaTML, 2025)