Diverse near neighbor problem. - Sofiane Abbar; Sihem Amer-Yahia; Piotr Indyk; Sepideh Mahabadi; Kasturi R. Varadarajan (SoCG, 2013)

Real-time recommendation of diverse related articles. - Sofiane Abbar; Sihem Amer-Yahia; Piotr Indyk; Sepideh Mahabadi (WWW, 2013)

Composable core-sets for diversity and coverage maximization. - Piotr Indyk; Sepideh Mahabadi; Mohammad Mahdian; Vahab S. Mirrokni (PODS, 2014)

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

Approximate Nearest Line Search in High Dimensions. - Sepideh Mahabadi (SODA, 2015)

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

Simultaneous Nearest Neighbor Search. - Piotr Indyk; Robert D. Kleinberg; Sepideh Mahabadi; Yang Yuan (SoCG, 2016)

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)

Proximity in the Age of Distraction: Robust Approximate Nearest Neighbor Search. - Sariel Har-Peled; Sepideh Mahabadi (SODA, 2017)

LSH on the Hypercube Revisited. - Sariel Har-Peled; Sepideh Mahabadi (CoRR, 2017)

Sublinear algorithms for massive data problems. - Sepideh Mahabadi (2017)

Approximate Sparse Linear Regression. - Sariel Har-Peled; Piotr Indyk; Sepideh Mahabadi (ICALP, 2018)

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

Nonlinear dimension reduction via outer Bi-Lipschitz extensions. - Sepideh Mahabadi; Konstantin Makarychev; Yury Makarychev; Ilya P. Razenshteyn (STOC, 2018)

Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. - Sepideh Mahabadi; Piotr Indyk; Shayan Oveis Gharan; Alireza Rezaei 001 (ICML, 2019)

Near Neighbor: Who is the Fairest of Them All? - Sariel Har-Peled; Sepideh Mahabadi (NeurIPS, 2019)

Streaming Complexity of SVMs. - Alexandr Andoni; Collin Burns; Yi Li 002; Sepideh Mahabadi; David P. Woodruff (APPROX-RANDOM, 2020)

Towards Better Approximation of Graph Crossing Number. - Julia Chuzhoy; Sepideh Mahabadi; Zihan Tan (FOCS, 2020)

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

Composable Core-sets for Determinant Maximization Problems via Spectral Spanners. - Piotr Indyk; Sepideh Mahabadi; Shayan Oveis Gharan; Alireza Rezaei 001 (SODA, 2020)

Non-adaptive adaptive sampling on turnstile streams. - Sepideh Mahabadi; Ilya P. Razenshteyn; David P. Woodruff; Samson Zhou (STOC, 2020)

Two-Sided Kirszbraun Theorem. - Arturs Backurs; Sepideh Mahabadi; Konstantin Makarychev; Yury Makarychev (SoCG, 2021)

Fair near neighbor search via sampling. - Martin Aumüller 001; Sariel Har-Peled; Sepideh Mahabadi; Rasmus Pagh; Francesco Silvestri 001 (SIGMOD Rec., 2021)

Adaptive Sketches for Robust Regression with Importance Sampling. - Sepideh Mahabadi; David P. Woodruff; Samson Zhou (APPROX/RANDOM, 2022)

Sampling near neighbors in search for fairness. - Martin Aumüller 001; Sariel Har-Peled; Sepideh Mahabadi; Rasmus Pagh; Francesco Silvestri 001 (Commun. ACM, 2022)

Composable Coresets for Constrained Determinant Maximization and Beyond. - Sepideh Mahabadi; Thuy-Duong Vuong (CoRR, 2022)

Sampling a Near Neighbor in High Dimensions - Who is the Fairest of Them All? - Martin Aumüller 001; Sariel Har-Peled; Sepideh Mahabadi; Rasmus Pagh; Francesco Silvestri 001 (ACM Trans. Database Syst., 2022)

Improved Diversity Maximization Algorithms for Matching and Pseudoforest. - Sepideh Mahabadi; Shyam Narayanan (APPROX/RANDOM, 2023)

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

Differentially Private Approximate Near Neighbor Counting in High Dimensions. - Alexandr Andoni; Piotr Indyk; Sepideh Mahabadi; Shyam Narayanan (NeurIPS, 2023)

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

Composable Coresets for Determinant Maximization: Greedy is Almost Optimal. - Siddharth Gollapudi; Sepideh Mahabadi; Varun Sivashankar (NeurIPS, 2023)

Core-sets for Fair and Diverse Data Summarization. - Sepideh Mahabadi; Stojan Trajanovski (NeurIPS, 2023)

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

Efficiently Computing Similarities to Private Datasets. - Arturs Backurs; Zinan Lin 001; Sepideh Mahabadi; Sandeep Silwal; Jakub Tarnawski (ICLR, 2024)

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

A 0.51-Approximation of Maximum Matching in Sublinear n^{1.5} Time. - Sepideh Mahabadi; Mohammad Roghani; Jakub Tarnawski (ICALP, 2025)

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

Graph-Based Algorithms for Diverse Similarity Search. - Piyush Anand; Piotr Indyk; Ravishankar Krishnaswamy; Sepideh Mahabadi; Vikas C. Raykar; Kirankumar Shiragur; Haike Xu (CoRR, 2025)

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

A 0.51-Approximation of Maximum Matching in Sublinear n1.5 Time. - Sepideh Mahabadi; Mohammad Roghani; Jakub Tarnawski (CoRR, 2025)