Mohammad Hossein
Bateni
Principal Scientist and Director of Research
Google, New York
DBLP Google scholar Google research ACM DL arXiv

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Mohammad Hossein
Bateni
Principal Scientist and Director of Research
Google, New York
DBLP Google scholar Google research ACM DL arXiv

All publications

Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval
Deep learning ML efficiency
with Yanfei Chen, Jinsung Yoon, Devendra Singh Sachan, Qingze Wang, Vincent Cohen-Addad, Chen-Yu Lee and Tomas Pfister
  • EMNLP 2024, Conference on Empirical Methods in Natural Language Processing
Efficient Centroid-Linkage Clustering
Approximation algorithms Fundamental
with Laxman Dhulipala, Willem Fletcher, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram and Jakub Łącki
  • NeurIPS 2024, 38th Annual Conference on Neural Information Processing Systems
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
Deep learning ML efficiency
with Taisuke Yasuka, Kyriakos Axiotis, Thomas Fu and Vahab Mirrokni
  • NeurIPS 2024, 38th Annual Conference on Neural Information Processing Systems
Resilient k-Clustering
Approximation algorithms Fundamental Dynamic Large-scale
with Sara Ahmadian, Hossein Esfandiari, Ashkan Norouzi-Fard, Silvio Lattanzi and Morteza Monemizadeh
  • KDD 2024, The 30th International Conference on Knowledge Discovery and Data Mining
Improved Active Covering via Density-based Space Transformation
Approximation algorithms Fundamental ML efficiency Geometric
with Hossein Esfandiari, Samira Hossein Ghorban and Alipasha Montaseri
  • KDD 2024, The 30th International Conference on Knowledge Discovery and Data Mining
Metric Clustering and MST with Strong and Weak Distance Oracles
Approximation algorithms Fundamental
with Prathamesh Dharangutte, Rajesh Jayaram and Chen Wang
  • COLT 2024, The 37th Annual Conference on Learning Theory
It’s Hard to HAC with Average Linkage!
Approximation algorithms Fundamental
with Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram and Jakub Łącki
  • ICALP 2024, The 51st International Colloquium on Automata, Languages and Programming
A Scalable Algorithm for Individually Fair K-means Clustering
Approximation algorithms Fundamental
with Vincent Cohen-Addad, Alessandro Epasto and Silvio Lattanzi
  • AISTATS 2024, The 27th International Conference on Artificial Intelligence and Statistics
Gemini: A Family of Highly Capable Multimodal Models
Deep learning
with many authors
On Complexity of 1-Center in Various Metrics
Approximation algorithms Fundamental
with Amir Abboud, Vincent Cohen-Addad, Karthik C.S. and Saeed Seddighin
  • APPROX 2023, The 26th International Conference on Approximation Algorithms for Combinatorial Optimization Problems
Active Covering via Density-based Space Transformations
ML efficiency
with Hossein Esfandiari, Samira HosseinGhorban and Alipasha Montaseri
  • 4th Crowd Science Workshop — CANDLE: Collaboration of Humans and Learning Algorithms for Data Labeling, WSDM 2023
Preference Elicitation for Music Recommendations
ML efficiency
with Ofer Meshi, , Li Yang, Ben Scheetz, Yanli Cai, Corbyn Salisbury, Vikram Aggarwal and Craig Boutilier
  • ICML 2023, Machine Learning on Graphs Workshop at WSDM
Graph-Structured Crawling: Model and Approach
ML efficiency
with Lin Chen, Hossein Esfandiari and Sasan Tavakkol
  • MLoG 2023, Machine Learning on Graphs Workshop at WSDM
Data Sampling using Locality Sensitive Hashing for Large Scale Graph Learning
ML efficiency
with Sarath Shekkizhar, Neslihan Bulut, Mohamed Farghal, Sasan Tavakkol and Animesh Nandi
  • MLG 2023, the 19th International Workshop on Mining and Learning with Graphs
Agile Modeling: From Concept to Classifier in Minutes
ML efficiency Deep learning
with Otilia Stretcu, Edward Vendrow, Kenji Hata, Krishnamurthy Viswanathan, Vittorio Ferrari, Sasan Tavakkol, Wenlei Zhou, Aditya Avinash, Enming Luo, Neil Gordon Alldrin, Gabriel Berger, Andrew Bunner, Chun-Ta Lu, Javier A. Rey, Giulia DeSalvo, Ranjay Krishna and Ariel Fuxman
  • ICCV 2023, International Conference on Computer Vision
  • NeurIPS 2023 Workshop: Adaptive Experimental Design and Active Learning in the Real World
Sequential Attention for Feature Selection
ML efficiency Deep learning
with Taisuke Yasuka, Lin Chen, Matthew Fahrbach, Thomas Fu and Vahab Mirrokni
  • ICLR 2023, The Eleventh International Conference on Learning Representations
Optimal Fully Dynamic k-Center Clustering for Adaptive and Oblivious Adversaries
Dynamic Fundamental
with Hossein Esfandiari, Hendrik Fichtenberger, Monika Henzinger, Rajesh Jayaram, Vahab Mirrokni and Andreas Wiese
  • SODA 2023, the 34th ACM-SIAM Symposium on Discrete Algorithms
Tackling Provably Hard Representative Selection via Graph Neural Networks
ML efficiency Deep learning
with Seyyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, Deepak Ramachandran, Bryan Perozzi and Vahab Mirrokni
  • TMLR 2023, Transactions on Machine Learning Research
SubMix: Learning to Mix Graph Sampling Heuristics
ML efficiency Deep learning
with Sami Abu-El-Haija, Joshua V. Dillon, Bahare Fatemi, Kyriakos Axiotis, Neslihan Bulut, and Bryan Perozzi
  • UAI 2023, the 39th Conference on Uncertainty in Artificial Intelligence
Efficient Distributed Algorithms for Minimum Spanning Tree in Dense Graphs
Large-scale Dynamic Fundamental
with Morteza Monemizadeh and Kees Voorintholt
  • ICDM 2022 Workshop on Incremental Learning
Streaming Belief Propagation for Community Detection
Large-scale Dynamic
with Yuchen Wu, André Linhares, Filipe Miguel Gonçalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard and Yakab Tardos
  • NeurIPS 2021, 35th Annual Conference on Neural Information Processing Systems
Extreme k-Center Clustering
Large-scale Fundamental
with Hossein Esfandiari, Manuela Fischer and Vahab Mirrokni
  • AAAI 2021, 35th Annual Conference on Neural Information Processing Systems
Introduction to the Special Issue for SPAA17
Large-scale
with MohammadTaghi Hajiaghayi and Silvio Lattanzi
  • ACM Trans. Parallel Comput. 6(3): 10:1 (2019)
Categorical Feature Compression via Submodular Optimization
Approximation algorithms Large-scale Fundamental
with Hossein Esfandiari, Lin Chen, Thomas Fu, Vahab Mirrokni and Afshin Rostamizadeh
  • ICML 2019, 36th International Conference on Machine Learning
Distributed Weighted Matching via Randomized Composable Coresets
Approximation algorithms Large-scale Fundamental
with Sepehr Assadi and Vahab Mirrokni
  • ICML 2019, 36th International Conference on Machine Learning
Cache-aware load balancing of data center applications
Network design Large-scale
with Aaron Archer, Kevin Aydin, Vahab Mirrokni, Aaron Schild, Ray Yang and Richard Zhuang
  • PVLDB, 12(6): 709-723, 2019
Polynomial-time Approximation Scheme for Minimum k-cut in Planar and Minor-free Graphs
Large-scale
with Alireza Farhadi and MohammadTaghi Hajiaghayi
  • SODA 2019, 30th Annual ACM-SIAM Symposium on Discrete Algorithms
Coresets Meet EDCS: Algorithms for Matching and Vertex Cover on Massive Graphs
Large-scale
with Sepehr Assadi, Aaron Bernstein, Vahab Mirrokni and Cliff Stein
  • SODA 2019, 30th Annual ACM-SIAM Symposium on Discrete Algorithms
Optimal Distributed Submodular Optimization via Sketching
Large-scale
with Hossein Esfandiari and Vahab Mirrokni
  • KDD 2018, 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
MapReduce Algorithms for Massive Trees
Large-scale
with Soheil Behnezhad, Mahsa Derakhshan, MohammadTaghi Hajiaghayi and Vahab Mirrokni
  • ICALP 2018, 45th International Colloquium on Automata, Languages, and Programming
Fast Algorithms for Knapsack via Convolution and Prediction
Fundamental
with MohammadTaghi Hajiaghayi, Saeed Seddighin and Cliff Stein
  • STOC 2018, 50th Annual ACM Symposium on the Theory of Computing
Optimal algorithms for coverage problems on massive data
Large-scale
with Hossein Esfandiari and Vahab Mirrokni
  • DISCML 2017, NIPS Workshop on Discrete Structures in Machine Learning
On Distributed Hierarchical Clustering
Large-scale
with Soheil Behnezhad, Mahsa Derakhshan, MohammadTaghi Hajiaghayi, Raimondas Kiveris, Silvio Lattanzi and Vahab Mirrokni
  • NIPS 2017, 30th Annual Conference on Advances in Neural Information Processing Systems
Almost optimal streaming algorithms for coverage problems
Large-scale
with Hossein Esfandiari and Vahab Mirrokni
  • SPAA 2017, 29th ACM Symposium on Parallelism in Algorithms and Architectures
A study of compact reserve pricing languages
Algorithmic game theory
with Hossein Esfandiari, Vahab Mirrokni and Saeed Seddighin
  • AAAI 2017, 31st AAAI Conference on Artificial Intelligence
Fair Resource Allocation in A Volatile Marketplace
Algorithmic game theory
with Yiwei Chen, Dragos Florin Ciocan and Vahab Mirrokni
  • EC 2016, 17th ACM Conference on Economics and Computation
  • NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services
  • Oper. Res. 70(1): 288-308 (2022)
A PTAS for planar group Steiner tree via spanner bootstrapping and prize collecting
PTAS Planar Network design Price-collecting clustering
with Erik D. Demaine, MohammadTaghi Hajiaghayi and Dániel Marx
  • STOC 2016, 48th Annual ACM SIGACT Symposium on Theory of Computing
Distributed Balanced Partitioning via Linear Embedding
Large-scale
with Kevin Aydin and Vahab Mirrokni
  • WSDM 2016, Ninth ACM International Conference on Web Search and Data Mining
  • Algorithms 2019, 12(8), 162
  • Google AI Blog (March 14, 2018)
Secretary Problems and Online Auctions
Algorithmic game theory
  • Encyclopedia of Algorithms 2016
Revenue Maximization for Selling Multiple Correlated Items
Algorithmic game theory
with Sina Dehghani, MohammadTaghi Hajiaghayi and Saeed Seddighin
  • ESA 2015, 23rd Annual European Symposium of Algorithms
Distributed Balanced Clustering via Mapping Coresets
Large-scale
with Aditya Bhaskara, Silvio Lattanzi and Vahab Mirrokni
  • NIPS 2014, 27th Annual Conference on Advances in Neural Information Processing Systems
Multiplicative Bidding in Online Advertising
Algorithmic game theory Approximation algorithms
with Jon Feldman, Vahab Mirrokni and Sam Chui-wai Wong
  • EC 2014, 15th ACM Conference on Economics and Computation
Concise Bid Optimization Strategies with Multiple Budget Constraints
Algorithmic game theory Approximation algorithms PTAS
with Arash Asadpour, Kshipra Bhawalkar and Vahab Mirrokni
  • WINE 2014, 10th International Conference on Web and Internet Economics
  • Management Science 2019
Network Cournot Competition
Algorithmic game theory
with Melika Abolhassani, Hamid Mahini, MohammadTaghi Hajiaghayi and Anshul Sawant
  • WINE 2014, 10th International Conference on Web and Internet Economics
Revenue Maximization with Nonexcludable Goods
Algorithmic game theory
with Nima Haghpanah, Balasubramanian Sivan and Morteza Zadimoghaddam
  • WINE 2013, Ninth International Conference of Web and Internet Economics
  • ACM Transactions of Economics and Computing 3(4): 18 (2015)
Improved Approximation Algorithms for (Budgeted) Node-Weighted Steiner Problems
Approximation algorithms Network design
with MohammadTaghi Hajiaghayi and Vahid Liaghat
  • ICALP 2013, 40th International Colloquium on Automata, Languages, and Programming
  • SIAM Journal on Computing, Volume 47, Issue 4, pp. 1275-1293
A polynomial-time approximation scheme for planar multiway cut
PTAS Planar Network design Price-collecting clustering
with MohammadTaghi Hajiaghayi, Philip N. Klein and Claire Mathieu
  • SODA 2012, 23rd Annual ACM-SIAM Symposium on Discrete Algorithms
Towards an efficient algorithmic framework for pricing cellular data service
Algorithmic game theory
with MohammadTaghi Hajiaghayi, Sina Jafarpour and Dan Pei
  • INFOCOM 2011, 30th Annual Conference of the IEEE Communications Society
Prize-collecting network design on planar graphs
PTAS Approximation algorithms Planar Network design Price-collecting clustering
with MohammadTaghi Hajiaghayi and Dániel Marx ,
and Chandra Chekuri, Alina R. Ene and Nitish Korula (merged)
  • SODA 2011, 22nd Annual ACM-SIAM Symposium on Discrete Algorithms
The submodular secretary problem and its extensions
Approximation algorithms
with MohammadTaghi Hajiaghayi and Morteza Zadimoghaddam
  • APPROX 2010, 13th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems
  • ACM Trans. Algorithms 9(4): 32 (2013)
Approximation Algorithms for the Directed k-Stroll and k-Tour Problems
Approximation algorithms Network design
with Julia Chuzhoy
  • APPROX 2010, 13th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems
  • Algorithmica 65(3): 545-561 (2013)
Cooperative game theory foundations of network bargaining games
Algorithmic game theory
with MohammadTaghi Hajiaghayi, Nicole Immorlica and Hamid Mahini
  • ICALP 2010, 37th International Colloquium on Automata, Languages and Programming
PTASes for Steiner forest on planar graphs and graphs of bounded treewidth
PTAS Planar Network design Price-collecting clustering
with MohammadTaghi Hajiaghayi and Dániel Marx
  • STOC 2010, 42nd ACM Symposium on Theory of Computing
  • Journal of the ACM 58(5): 21 (2011)
Euclidean Prize-collecting Steiner Forest
PTAS Geometric Network design
with MohammadTaghi Hajiaghayi
  • LATIN 2010, 9th Latin American Theoretical Informatics Symposium
  • Algorithmica 62(3-4): 906-929 (2012)
Improved Approximation Algorithms for Prize-Collecting Steiner Tree and TSP
Approximation algorithms Network design Price-collecting clustering
with Aaron Archer, MohammadTaghi Hajiaghayi and Howard Karloff
  • FOCS 2009, 50th Annual IEEE Symposium on Foundations of Computer Science
  • SIAM Journal on Computing, Volume 40, Issue 2, pp. 309-332
A note on the subadditive network design problem
Approximation algorithms Network design
with MohammadTaghi Hajiaghayi
  • Operations Research Letters, Volume 37, Issue 5, Sept. 2009, pp. 339-344
New Approximation Algorithms for Degree Lower-bounded Arborescences and Max-Min Allocation
Approximation algorithms Fair allocation
with Moses Charikar and Venkatesan Guruswami
  • Technical Report TR-848-09, March 2009, Department of Computer Science, Princeton University
Minimizing Staleness and Stretch in Real-Time Data Ware-houses
Scheduling
with Lukasz Golab, MohammadTaghi Hajiaghayi and Howard Karloff
  • SPAA 2009, 21st ACM Symposium on Parallelism in Algorithms and Architectures
  • Theory of Computing Systems [Special Issue on SPAA 2009], Volume 49, Number 4, pp. 757-780 (2011)
MaxMin allocation via degree lower-bounded arborescences
Approximation algorithms Fair allocation
with Moses Charikar and Venkatesan Guruswami
  • STOC 2009, 41st ACM Symposium on Theory of Computing
Multi-VPN Optimization for Scalable Routing via Relaying
Network design
with Alexandre Gerber, MohammadTaghi Hajiaghayi and Subhabrata Sen
  • INFOCOM 2009, 28th Annual Conference of the IEEE Communications Society
  • IEEE/ACM Transactions on Networking, Volume 18, Number 5, pp. 1544-1556
Assignment problem in content distribution networks: unsplittable hard-capacitated facility location
PTAS Network design
with MohammadTaghi Hajiaghayi
  • SODA 2009, 20th Annual ACM-SIAM Symposium on Discrete Algorithms
  • ACM Transactions of Algorithms 8(3): 20 (2012)
Plane Embedding of Planar Graph Metrics
Planar Geometric
with Erik D. Demaine, MohammadTaghi Hajiaghayi and Mohammad Moharrami
  • SoCG 2006, 22nd Annual ACM Symposium on Computational Geometry
  • Journal of Discrete and Computational Geometry, Volume 38, Number 3, pp. 615-637