Vahab S. Mirrokni

Publication Activity (10 Years)

Years Active: 2000-2022
Publications (10 Years): 190

Top Venues

CoRR

ICML

SODA

Publications

Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii
Label differential privacy via clustering. AISTATS (2022)
MohammadHossein Bateni, Yiwei Chen, Dragos Florin Ciocan, Vahab S. Mirrokni
Fair Resource Allocation in a Volatile Marketplace. Oper. Res. 70 (1) (2022)
Sara Ahmadian, Hossein Esfandiari, Vahab S. Mirrokni, Binghui Peng
Robust Load Balancing with Machine Learned Advice. SODA (2022)
Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni, Balasubramanian Sivan
From Online Optimization to PID Controllers: Mirror Descent with Momentum. CoRR (2022)
Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Munoz, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR (2022)
Vincent Cohen-Addad, Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan
Improved Approximations for Euclidean k-means and k-median, via Nested Quasi-Independent Sets. CoRR (2022)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. SODA (2022)
Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab S. Mirrokni
Tackling Provably Hard Representative Selection via Graph Neural Networks. CoRR (2022)
Sepehr Assadi, Vaggos Chatziafratis, Jakub Lacki, Vahab S. Mirrokni, Chen Wang
Hierarchical Clustering in Graph Streams: Single-Pass Algorithms and Space Lower Bounds. CoRR (2022)
Hossein Esfandiari, Alessandro Epasto, Vahab S. Mirrokni, Andres Muñoz Medina, Sergei Vassilvitskii
Smooth Anonymity for Sparse Binary Matrices. CoRR (2022)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. SODA (2022)
Oleksandr Ferludin, Arno Eigenwillig, Martin Blais, Dustin Zelle, Jan Pfeifer, Alvaro Sanchez-Gonzalez, Wai Lok Sibon Li, Sami Abu-El-Haija, Peter W. Battaglia, Neslihan Bulut, Jonathan Halcrow, Filipe Miguel Gonçalves de Almeida, Silvio Lattanzi, André Linhares, Brandon Mayer, Vahab S. Mirrokni, John Palowitch, Mihir Paradkar, Jennifer She, Anton Tsitsulin, Kevin Villela, Lisa Wang, David Wong, Bryan Perozzi
TF-GNN: Graph Neural Networks in TensorFlow. CoRR (2022)
Shyam Narayanan, Vahab S. Mirrokni, Hossein Esfandiari
Tight and Robust Private Mean Estimation with Few Users. ICML (2022)
Santiago R. Balseiro, Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo
Optimal Mechanisms for Value Maximizers with Budget Constraints via Target Clipping. EC (2022)
Vincent Cohen-Addad, Vahab S. Mirrokni, Peilin Zhong
Massively Parallel k-Means Clustering for Perturbation Resilient Instances. ICML (2022)
Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan
Almost Tight Approximation Algorithms for Explainable Clustering. SODA (2022)
Vincent Cohen-Addad, Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan
-median, via nested quasi-independent sets. STOC (2022)
Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni
Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems. ALT (2022)
Jessica Shi, Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab S. Mirrokni
Scalable Community Detection via Parallel Correlation Clustering. Proc. VLDB Endow. 14 (11) (2021)
Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni
Regret Bounds for Batched Bandits. AAAI (2021)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab S. Mirrokni
Bidding and Pricing in Budget and ROI Constrained Markets. CoRR (2021)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Vahab S. Mirrokni, Warren Schudy
Massively Parallel Computation via Remote Memory Access. ACM Trans. Parallel Comput. 8 (3) (2021)
Negin Golrezaei, Adel Javanmard, Vahab S. Mirrokni
Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions. Oper. Res. 69 (1) (2021)
Santiago R. Balseiro, Anthony Kim, Mohammad Mahdian, Vahab S. Mirrokni
Budget-Management Strategies in Repeated Auctions. Oper. Res. 69 (3) (2021)
Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan
Parallelizing Thompson Sampling. NeurIPS (2021)
MohammadHossein Bateni, Hossein Esfandiari, Rajesh Jayaram, Vahab S. Mirrokni
Optimal Fully Dynamic k-Centers Clustering. CoRR (2021)
Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, C. J. Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab S. Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, Shuo Wang
Clustering for Private Interest-based Advertising. KDD (2021)
Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
Regularized Online Allocation Problems: Fairness and Beyond. ICML (2021)
Santiago R. Balseiro, Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo
Robust Auction Design in the Auto-bidding World. NeurIPS (2021)
Santiago R. Balseiro, Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo
Robust Auction Design in the Auto-bidding World. CoRR (2021)
MohammadHossein Bateni, Hossein Esfandiari, Manuela Fischer, Vahab S. Mirrokni
Extreme k-Center Clustering. AAAI (2021)
Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni
Adaptivity in Adaptive Submodularity. COLT (2021)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. CoRR (2021)
Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan
Almost Tight Approximation Algorithms for Explainable Clustering. CoRR (2021)
Anthony Kim, Vahab S. Mirrokni, Hamid Nazerzadeh
Deals or No Deals: Contract Design for Online Advertising. Oper. Res. 69 (5) (2021)
Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan
Parallelizing Thompson Sampling. CoRR (2021)
Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab S. Mirrokni, Jessica Shi
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time. ICML (2021)
Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii
Label differential privacy via clustering. CoRR (2021)
Santiago R. Balseiro, Vahab S. Mirrokni, Renato Paes Leme, Song Zuo
Non-Excludable Dynamic Mechanism Design. SODA (2021)
Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab S. Mirrokni, Jessica Shi
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time. CoRR (2021)
Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo
Towards Efficient Auctions in an Auto-bidding World. CoRR (2021)
Yuan Deng, Sébastien Lahaie, Vahab S. Mirrokni, Song Zuo
Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing. ICML (2021)
Santiago R. Balseiro, Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo
The Landscape of Auto-bidding Auctions: Value versus Utility Maximization. EC (2021)
Shipra Agrawal, Eric Balkanski, Vahab S. Mirrokni, Balasubramanian Sivan
Robust Repeated First Price Auctions. EC (2021)
Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo
Towards Efficient Auctions in an Auto-bidding World. WWW (2021)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. CoRR (2021)
Lin Chen, Hossein Esfandiari, Gang Fu, Vahab S. Mirrokni, Qian Yu
Feature Cross Search via Submodular Optimization. CoRR (2021)
Lin Chen, Hossein Esfandiari, Gang Fu, Vahab S. Mirrokni, Qian Yu
Feature Cross Search via Submodular Optimization. ESA (2021)
Yuan Deng, Vahab S. Mirrokni, Song Zuo
Non-Clairvoyant Dynamic Mechanism Design with Budget Constraints and Beyond. EC (2021)
Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sébastien Lahaie, Miles Lubin, Vahab S. Mirrokni, Jann Spiess, Guido Imbens
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls. NeurIPS (2021)
Negin Golrezaei, Max Lin, Vahab S. Mirrokni, Hamid Nazerzadeh
Boosted Second Price Auctions: Revenue Optimization for Heterogeneous Bidders. KDD (2021)
Quanquan Gu, Amin Karbasi, Khashayar Khosravi, Vahab S. Mirrokni, Dongruo Zhou
Batched Neural Bandits. CoRR (2021)
Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan
Tight and Robust Private Mean Estimation with Few Users. CoRR (2021)
Hossein Esfandiari, Vahab S. Mirrokni, Peilin Zhong
Almost Linear Time Density Level Set Estimation via DBSCAN. AAAI (2021)
Jessica Shi, Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab S. Mirrokni
Scalable Community Detection via Parallel Correlation Clustering. CoRR (2021)
Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni
Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems. CoRR (2020)
Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni
The Landscape of Nonconvex-Nonconcave Minimax Optimization. CoRR (2020)
Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
Regularized Online Allocation Problems: Fairness and Beyond. CoRR (2020)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Vahab S. Mirrokni, Warren Schudy
Parallel Graph Algorithms in Constant Adaptive Rounds: Theory meets Practice. CoRR (2020)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Vahab S. Mirrokni, Warren Schudy
Parallel Graph Algorithms in Constant Adaptive Rounds: Theory meets Practice. Proc. VLDB Endow. 13 (13) (2020)
Negin Golrezaei, Adel Javanmard, Vahab S. Mirrokni
Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctions. CoRR (2020)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Manolis Zampetakis
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions. CoRR (2020)
Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
Dual Mirror Descent for Online Allocation Problems. ICML (2020)
Thodoris Lykouris, Vahab S. Mirrokni, Renato Paes Leme
Bandits with Adversarial Scaling. ICML (2020)
Joey Huchette, Haihao Lu, Hossein Esfandiari, Vahab S. Mirrokni
Contextual Reserve Price Optimization in Auctions via Mixed Integer Programming. NeurIPS (2020)
Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni
Accelerating Gradient Boosting Machines. AISTATS (2020)
Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems. CoRR (2020)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Emmanouil Zampetakis
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions. NeurIPS (2020)
Thodoris Lykouris, Vahab S. Mirrokni, Renato Paes Leme
Bandits with adversarial scaling. CoRR (2020)
Gagan Goel, Vahab S. Mirrokni, Renato Paes Leme
Clinching auctions with online supply. Games Econ. Behav. 123 (2020)
Santiago R. Balseiro, Anthony Kim, Mohammad Mahdian, Vahab S. Mirrokni
Budget-Constrained Incentive Compatibility for Stationary Mechanisms. EC (2020)
Yuan Deng, Sébastien Lahaie, Vahab S. Mirrokni
Robust Pricing in Dynamic Mechanism Design. ICML (2020)
Soheil Behnezhad, Jakub Lacki, Vahab S. Mirrokni
Update Time. SODA (2020)
Mahsa Derakhshan, Negin Golrezaei, Vahideh H. Manshadi, Vahab S. Mirrokni
Product Ranking on Online Platforms. EC (2020)
Alessandro Epasto, Mohammad Mahdian, Jieming Mao, Vahab S. Mirrokni, Lijie Ren
Smoothly Bounding User Contributions in Differential Privacy. NeurIPS (2020)
Joey Huchette, Haihao Lu, Hossein Esfandiari, Vahab S. Mirrokni
Contextual Reserve Price Optimization in Auctions. CoRR (2020)
Yuan Deng, Sébastien Lahaie, Vahab S. Mirrokni, Song Zuo
A Data-Driven Metric of Incentive Compatibility. WWW (2020)
David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab S. Mirrokni, Amir Najmi
Randomized Experimental Design via Geographic Clustering. KDD (2019)
Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni
Adaptivity in Adaptive Submodularity. CoRR (2019)
Sepehr Assadi, MohammadHossein Bateni, Vahab S. Mirrokni
Distributed Weighted Matching via Randomized Composable Coresets. ICML (2019)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Warren Schudy, Vahab S. Mirrokni
Massively Parallel Computation via Remote Memory Access. CoRR (2019)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Vahab S. Mirrokni
Near-Optimal Massively Parallel Graph Connectivity. FOCS (2019)
Alessandro Epasto, Vahab S. Mirrokni, Morteza Zadimoghaddam
Scalable Diversity Maximization via Small-size Composable Core-sets (Brief Announcement). SPAA (2019)
Maxime C. Cohen, Philipp W. Keller, Vahab S. Mirrokni, Morteza Zadimoghaddam
Overcommitment in Cloud Services: Bin Packing with Chance Constraints. Manag. Sci. 65 (7) (2019)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Vahab S. Mirrokni
Near-Optimal Massively Parallel Graph Connectivity. CoRR (2019)
Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond. CoRR (2019)
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Lacki, Vahab S. Mirrokni, Warren Schudy
Massively Parallel Computation via Remote Memory Access. SPAA (2019)
Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni
Batched Multi-Armed Bandits with Optimal Regret. CoRR (2019)
Kevin Aydin, MohammadHossein Bateni, Vahab S. Mirrokni
Distributed Balanced Partitioning via Linear Embedding. Algorithms 12 (8) (2019)
Santiago R. Balseiro, Vahab S. Mirrokni, Renato Paes Leme, Song Zuo
Dynamic Double Auctions: Towards First Best. SODA (2019)
MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh
Categorical Feature Compression via Submodular Optimization. CoRR (2019)
Shipra Agrawal, Eric Balkanski, Vahab S. Mirrokni, Balasubramanian Sivan
Dynamic First Price Auctions Robust to Heterogeneous Buyers. CoRR (2019)
Arash Asadpour, MohammadHossein Bateni, Kshipra Bhawalkar, Vahab S. Mirrokni
Concise Bid Optimization Strategies with Multiple Budget Constraints. Manag. Sci. 65 (12) (2019)
Jean Pouget-Abadie, Kevin Aydin, Warren Schudy, Kay Brodersen, Vahab S. Mirrokni
Variance Reduction in Bipartite Experiments through Correlation Clustering. NeurIPS (2019)
Lin Chen, Hossein Esfandiari, Gang Fu, Vahab S. Mirrokni
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond. NeurIPS (2019)
Gagan Goel, Vahab S. Mirrokni, Renato Paes Leme
Pareto Efficient Auctions with Interest Rates. AAAI (2019)
Hossein Esfandiari, Vahab S. Mirrokni, Peilin Zhong
Streaming Balanced Clustering. CoRR (2019)
Soheil Behnezhad, Jakub Lacki, Vahab S. Mirrokni
Update Time. CoRR (2019)
Sepehr Assadi, MohammadHossein Bateni, Vahab S. Mirrokni
Distributed Weighted Matching via Randomized Composable Coresets. CoRR (2019)
Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni
Accelerating Gradient Boosting Machine. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Vahab S. Mirrokni