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Publications:
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Online Steiner Forest with Recourse,
Yaowei Long, Sepideh Mahabadi, Sherry Sarkar, Jakub Tarnawski,
ICALP 2026.
- The General Expiration Streaming Model: Diameter, k-Center, Counting, Sampling, and Friends,
Lotte Blank, Sergio Cabello, MohammadTaghi Hajiaghayi, Robert Krauthgamer, Sepideh Mahabadi, André Nusser, Jeff M. Phillips, Jonas Sauer
ICALP 2026.
(pdf)
- Composable Coresets for Constrained Determinant Maximization and Beyond,
Sepideh Mahabadi, Thuy-Duong Vuong,
AISTATS 2026 (Spotlight).
(pdf)
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Sublinear Metric Steiner Forest via Maximal Independent Set,
Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski, Ali Vakilian,
SODA 2026.
(pdf)
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Improved Algorithms for Fair Matroid Submodular Maximization,
Sepideh Mahabadi, Sherry Sarkar, Jakub Tarnawski,
NeurIPS 2025.
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Streaming Algorithms for Network Design,
Chandra Chekuri, Rhea Jain, Sepideh Mahabadi, Ali Vakilian,
APPROX 2025.
(pdf)
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Graph-Based Algorithms for Diverse Similarity Search,
Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy, Sepideh Mahabadi, Vikas C. Raykar, Kirankumar Shiragur, Haike Xu,
ICML 2025.
(pdf)
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A 0.51-Approximation of Maximum Matching in Sublinear n1.5 Time,
Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski,
ICALP 2025.
(pdf,
talk by Jakub)
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Guessing Efficiently for Constrained Subspace Approximation,
Aditya Bhaskara, Sepideh Mahabadi, Madhusudhan Pittu, Ali Vakilian, David Woodruff,
ICALP 2025.
(pdf)
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Sublinear Metric Steiner Tree via Improved Bounds for Set Cover,
Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski, Ali Vakilian,
ITCS 2025.
(pdf,
slides
,
talk by Mohammad)
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Streaming Algorithms for Connectivity Augmentation,
Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian,
ICALP 2024.
(pdf)
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Efficiently Computing Similarities to Private Datasets,
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024.
(pdf)
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Differentially Private Approximate Near Neighbor Counting in High Dimensions,
Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan,
NeurIPS 2023 (Spotlight).
(pdf)
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Core-sets for Fair and Diverse Data Summarization,
Sepideh Mahabadi, Stojan Trajanovski,
NeurIPS 2023.
(pdf)
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Tight Bounds for Volumetric Spanners and Applications,
Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian,
NeurIPS 2023.
(pdf,
talk by Ali)
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Composable Coresets for Determinant Maximization: Greedy is Almost Optimal,
Siddharth Gollapudi, Sepideh Mahabadi, Varun Sivashankar
NeurIPS 2023.
(pdf)
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Improved Diversity Maximization Algorithms for Matching and Pseudoforest,
Sepideh Mahabadi, Shyam Narayanan,
APPROX 2023.
(pdf)
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Approximation Algorithms for Fair Range Clustering,
Sedjro Hotegni, Sepideh Mahabadi, Ali Vakilian,
ICML 2023.
(pdf,
short talk by Ali)
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Adaptive Sketches for Robust Regression with Importance Sampling,
Sepideh Mahabadi, David Woodruff, Samson Zhou,
RANDOM 2022.
(pdf,
talk by Samson)
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Sampling a Near Neighbor in High Dimensions--Who is the Fairest of Them All?
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri,
(Extended version, based on our paper in NeurIPS '19 and the paper of Aumüller, Pagh, and Silvestri in PODS '20)
CACM 2022,
TODS 2022,
SIGMOD Record 2021.
(pdf,
slides)
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Two-sided Kirszbraun Theorem,
Arturs Backurs, Sepideh Mahabadi, Konstantin Makarychev, Yury Makarychev,
SoCG 2021.
(pdf,
slides)
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Towards Better Approximation of Graph Crossing Number,
Julia Chuzhoy, Sepideh Mahabadi, Zihan Tan,
FOCS 2020.
(pdf,
talk by Zihan
)
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Streaming Complexity of SVMs,
Alexandr Andoni, Collin Burns, Yi Li, Sepideh Mahabadi, David Woodruff,
APPROX 2020.
(pdf,
talk by Collin)
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Individual Fairness for k-Clustering,
Sepideh Mahabadi, Ali Vakilian,
ICML 2020.
(pdf,
talk by Ali)
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Non-Adaptive Adaptive Sampling on Turnstile Streams,
Sepideh Mahabadi, Ilya Razenshteyn, David Woodruff, Samson Zhou,
STOC 2020.
(pdf,
slides)
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Composable Core-sets for Determinant Maximization Problems via Spectral Spanners,
Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei,
SODA 2020.
(pdf,
slides)
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Near Neighbor: Who is the Fairest of Them All?,
Sariel Har-Peled, Sepideh Mahabadi,
NeurIPS 2019.
(pdf,
slides)
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Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm,
Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei,
ICML 2019 (Long Talk).
(pdf,
slides)
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Approximate Sparse Linear Regression,
Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi,
ICALP 2018.
(pdf,
slides)
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Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extensions,
Sepideh Mahabadi, Konstantin Makarychev, Yury Makarychev, Ilya Razenshteyn,
STOC 2018.
(pdf,
slides)
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Set Cover in Sub-linear Time,
Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee,
SODA 2018.
(pdf,
slides)
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Fractional Set Cover in the Streaming Model,
Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Jonathan Ullman, Ali Vakilian, Anak Yodpinyanee,
APPROX 2017.
(
pdf,
slides)
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Proximity in the Age of Distraction: Robust Approximate Nearest Neighbor Search,
Sariel Har-Peled, Sepideh Mahabadi,
SODA 2017.
(pdf,
slides)
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Towards Tight Bounds for the Streaming Set Cover Problem,
Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi, Ali Vakilian,
PODS 2016.
(pdf,
slides)
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Simultaneous Nearest Neighbor Search,
Piotr Indyk, Robert Kleinberg, Sepideh Mahabadi, Yang Yuan,
SoCG 2016.
(pdf,
slides)
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Approximate Nearest Line Search in High Dimensions,
Sepideh Mahabadi,
SODA 2015.
(pdf,
short slides,
long slides)
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On Streaming and Communication Complexity of the Set Cover Problem,
Erik Demaine, Piotr Indyk, Sepideh Mahabadi, Ali Vakilian,
DISC 2014.
(pdf)
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Composable Core-sets for Diversity and Coverage Maximization,
Piotr Indyk, Sepideh Mahabadi, Mohammad Mahdian, Vahab Mirrokni,
PODS 2014 (Test-of-Time Award).
(pdf, slides)
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Diverse Near Neighbor Problem,
Sofiane Abbar, Sihem Amer-Yahia, Piotr Indyk, Sepideh Mahabadi, Kasturi Varadarajan,
SoCG 2013.
(pdf , slides)
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Real-time Recommendation of Diverse Related Articles,
Sofiane Abbar, Sihem Amer-Yahia, Piotr Indyk, Sepideh Mahabadi,
WWW 2013.
(pdf)
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Recent Advances in Diversity Maximization in the Offline and Composable Coreset Models
- Dynamic Graphs and Algorithm Design Workshop at Simons Institute, September 2023
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Sampling a Near Neighbor in High Dimensions � Who is the Fairest of Them All?
- RAISE (Responsible AI and Software Experiences) at UW, November 2022
- Sublinear Algorithms Workshop, MIT, August 2022
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Non-Adaptive Adaptive Sampling in Turnstile Streams
- IDEAL Workshop on High-Dimensional Geometry and Analysis, May 2022
- Michigan-Purdue Theory Seminar, September 2020
- TCS+ Talk, April 2020
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Two-sided Kirszbraun Theorem
Workshop on Algorithms for Large Data, August 2021
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Diversity and Fairness in Data Summarization Algorithms
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ICPCU Alumni Lecture Series, June 2021
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IPM Combinatorics and Computing Conference (IPMCCC), May 2021
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EPFL, IC School, April 2021
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Columbia University, CS Department, April 2021
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University of Michigan, CSE Division, March 2021
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Google Research, March 2021
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CMU, CS Department, March 2021
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University of Maryland, CS Department, March 2021
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Purdue University, CS Department, February 2021
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Georgia Institute of Technology, School of CS, February 2021
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MSR Redmond, MLO and Algorithms groups, February 2021
- University of Waterloo, CS Department, Januray 2021
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Determinant Maximization over Large Data Sets
Sub-linear Reading Group, MIT, September 2020
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Composable Core-sets for the Determinant Maximization Problem
Rising Stars Talk, TCS Women Spotlight Workshop, June 2020
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Composable Core-sets for Determinant Maximization Problems via Spectral Spanners
- CMU, November 2019
- UIUC, February 2019
- Junior Theorists Workshop, Northwestern Univeristy, November 2018
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Diversity Maximization over Large Data Sets
- The Statistics and Data Sciences (SDS) Seminar Series, UT Austin, October 2022
- UCSB Theory Colloquium, April 2022
- MSR Redmond, October 2019
- Optimization Methods in Computer Vision and Image Processing workshop, ICERM, May 2019
- Midwest Theory Day, Purdue University, April 2019
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Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extension
- Metric Embeddings & Dimensionality Reduction workshop, Northwestern Univeristy, May 2019
- University of Chicago, October 2018
- Google New York, July 2018
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Set Cover in Sub-linear Time
- Workshop on Local Algorithms (WOLA), MIT, June 2018
- Rutgers Univeristy/DIMCAS, May 2018
- Midwest Theory Day, TTIC, April 2018
- New York Area Theory Day, NYU, December 2017
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Fractional Set Cover in the Streaming Model
Simons Collaboration on Algorithms & Geometry, February 2018
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Approximate Nearest Neighbor and Its Many Variants
- University of Washington, April 2017
- IBM Watson, December 2016
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Towards Tight Bounds for the Streaming Set Cover Problem
University of Toronto, November 2015
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Approximate Nearest Line Search in High Dimensions
Brown University, November 2014
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