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Author search results
Exact matches
- Vahab S. Mirrokni
aka: Vahab Mirrokni, Seyed Vahab Mirrokni
Google Research, New York City, USA
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Publication search results
found 420 matches
- 2024
- Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni:
Optimistic Rates for Learning from Label Proportions. COLT 2024: 3437-3474 - Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. SODA 2024: 3960-3996 - Hossein Esfandiari
, Praneeth Kacham
, Vahab Mirrokni
, David P. Woodruff
, Peilin Zhong
:
Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond. STOC 2024: 1911-1922 - Yuan Deng
, Negin Golrezaei
, Patrick Jaillet
, Jason Cheuk Nam Liang
, Vahab Mirrokni
:
Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice. WWW 2024: 267-275 - Yuan Deng
, Mohammad Mahdian
, Jieming Mao
, Vahab Mirrokni
, Hanrui Zhang
, Song Zuo
:
Efficiency of the Generalized Second-Price Auction for Value Maximizers. WWW 2024: 46-56 - Yuan Deng
, Jieming Mao
, Vahab Mirrokni
, Yifeng Teng
, Song Zuo
:
Non-uniform Bid-scaling and Equilibria for Different Auctions: An Empirical Study. WWW 2024: 256-266 - Paul Dütting
, Vahab Mirrokni
, Renato Paes Leme
, Haifeng Xu
, Song Zuo
:
Mechanism Design for Large Language Models. WWW 2024: 144-155 - Alessandro Epasto
, Hossein Esfandiari
, Vahab Mirrokni
, Andrés Muñoz Medina
:
Smooth Anonymity for Sparse Graphs. WWW (Companion Volume) 2024: 621-624 - Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu:
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions. CoRR abs/2401.11081 (2024) - Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni:
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses. CoRR abs/2402.04987 (2024) - Amir Zandieh, Insu Han, Vahab Mirrokni, Amin Karbasi:
SubGen: Token Generation in Sublinear Time and Memory. CoRR abs/2402.06082 (2024) - Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David P. Woodruff, Michael Wunder:
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond. CoRR abs/2402.17327 (2024) - Taisuke Yasuda, Kyriakos Axiotis, Gang Fu, MohammadHossein Bateni, Vahab Mirrokni:
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization. CoRR abs/2402.17902 (2024) - Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
Optimal Communication for Classic Functions in the Coordinator Model and Beyond. CoRR abs/2403.20307 (2024) - Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Seyed Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni:
Understanding Transformer Reasoning Capabilities via Graph Algorithms. CoRR abs/2405.18512 (2024) - Laxman Dhulipala, Majid Hadian, Rajesh Jayaram, Jason Lee, Vahab Mirrokni:
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings. CoRR abs/2405.19504 (2024) - Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni:
Optimistic Rates for Learning from Label Proportions. CoRR abs/2406.00487 (2024) - Hossein Esfandiari, Vahab Mirrokni, Praneeth Kacham, David P. Woodruff, Peilin Zhong:
High-Dimensional Geometric Streaming for Nearly Low Rank Data. CoRR abs/2406.02910 (2024) - Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong:
Perturb-and-Project: Differentially Private Similarities and Marginals. CoRR abs/2406.04868 (2024) - Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong:
Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR abs/2406.11206 (2024) - 2023
- Santiago R. Balseiro
, Haihao Lu
, Vahab Mirrokni:
The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems. Oper. Res. 71(1): 101-119 (2023) - Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni, Binghui Peng:
Robust Load Balancing with Machine Learned Advice. J. Mach. Learn. Res. 24: 44:1-44:46 (2023) - Santiago R. Balseiro
, Negin Golrezaei
, Mohammad Mahdian
, Vahab Mirrokni, Jon Schneider:
Contextual Bandits with Cross-Learning. Math. Oper. Res. 48(3): 1607-1629 (2023) - Benjamin Grimmer
, Haihao Lu, Pratik Worah, Vahab Mirrokni:
The landscape of the proximal point method for nonconvex-nonconcave minimax optimization. Math. Program. 201(1): 373-407 (2023) - CJ Carey
, Travis Dick
, Alessandro Epasto
, Adel Javanmard
, Josh Karlin
, Shankar Kumar
, Andres Muñoz Medina
, Vahab Mirrokni
, Gabriel Henrique Nunes
, Sergei Vassilvitskii
, Peilin Zhong
:
Measuring Re-identification Risk. Proc. ACM Manag. Data 1(2): 149:1-149:26 (2023) - Laxman Dhulipala
, Jakub Lacki
, Jason Lee, Vahab Mirrokni
:
TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs. Proc. ACM Manag. Data 1(3): 221:1-221:27 (2023) - Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni:
Pricing against a Budget and ROI Constrained Buyer. AISTATS 2023: 9282-9307 - Taisuke Yasuda, Mohammad Hossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni:
Sequential Attention for Feature Selection. ICLR 2023 - Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas:
Replicable Bandits. ICLR 2023 - Santiago R. Balseiro, Rachitesh Kumar, Vahab Mirrokni, Balasubramanian Sivan, Di Wang:
Robust Budget Pacing with a Single Sample. ICML 2023: 1636-1659
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