A. Rostamizadeh

Most-cited papers

Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, A. Rostamizadeh +1 more
2016Journal of machine learning research3,022 citations
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Domain Adaptation: Learning Bounds and Algorithms
Y. Mansour, M. Mohri, A. Rostamizadeh
2009Annual Conference Computational Learning Theory891 citations
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Algorithms for Learning Kernels Based on Centered Alignment
Corinna Cortes, M. Mohri, A. Rostamizadeh
2012Journal of machine learning research665 citations
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Domain Adaptation with Multiple Sources
Y. Mansour, M. Mohri, A. Rostamizadeh
2008Neural Information Processing Systems601 citations
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A System for Massively Parallel Hyperparameter Tuning
Liam Li, Kevin G. Jamieson, A. Rostamizadeh, E. Gonina +4 more
2018Conference on Machine Learning and Systems559 citations
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L2 Regularization for Learning Kernels
Corinna Cortes, M. Mohri, A. Rostamizadeh
2009Conference on Uncertainty in Artificial Intelligence523 citations
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Sample Selection Bias Correction Theory
Corinna Cortes, M. Mohri, M. Riley, A. Rostamizadeh
2008International Conference on Algorithmic Learning Theory371 citations Open access
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Learning Non-Linear Combinations of Kernels
Corinna Cortes, M. Mohri, A. Rostamizadeh
2009Neural Information Processing Systems325 citations
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Batch Active Learning at Scale
Gui Citovsky, Giulia DeSalvo, C. Gentile, Lazaros Karydas +3 more
2021Neural Information Processing Systems223 citations
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Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization
Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, A. Rostamizadeh +1 more
2016International Conference on Learning Representations206 citations
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Two-Stage Learning Kernel Algorithms
Corinna Cortes, M. Mohri, A. Rostamizadeh
2010International Conference on Machine Learning203 citations
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DistillSpec: Improving Speculative Decoding via Knowledge Distillation
Yongchao Zhou, Kaifeng Lyu, A. Rawat, A. Menon +4 more
2023International Conference on Learning Representations195 citations Open access
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Rademacher Complexity Bounds for Non-I.I.D. Processes
M. Mohri, A. Rostamizadeh
2008Neural Information Processing Systems195 citations
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Massively Parallel Hyperparameter Tuning
Liam Li, Kevin G. Jamieson, A. Rostamizadeh, E. Gonina +3 more
2018arXiv.org194 citations
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Foundations of Machine Learning
M. Mohri, A. Rostamizadeh, A. Talwalkar
2012Adaptive computation and machine learning179 citations Open access
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Stability Bounds for Stationary φ-mixing and β-mixing Processes
M. Mohri, A. Rostamizadeh
2008174 citations
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Learning Prices for Repeated Auctions with Strategic Buyers
Kareem Amin, A. Rostamizadeh, Umar Syed
2013Neural Information Processing Systems166 citations
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Multiple Source Adaptation and the Rényi Divergence
Y. Mansour, M. Mohri, A. Rostamizadeh
2009Conference on Uncertainty in Artificial Intelligence156 citations
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Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits
A. Rostamizadeh, A. Talwalkar, Giulia DeSalvo, Kevin G. Jamieson +1 more
2016arXiv.org149 citations
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Repeated Contextual Auctions with Strategic Buyers
Kareem Amin, A. Rostamizadeh, Umar Syed
2014Neural Information Processing Systems141 citations
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Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Maruan Al-Shedivat, Jennifer Gillenwater, E. Xing, A. Rostamizadeh
2020International Conference on Learning Representations134 citations
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An Analysis of SVD for Deep Rotation Estimation
Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely +3 more
2020Neural Information Processing Systems132 citations
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Balancing traffic load in wireless networks with curveball routing
Lucian Popa, A. Rostamizadeh, R. Karp, C. Papadimitriou +1 more
2007ACM Interational Symposium on Mobile Ad Hoc Networking and Computing131 citations
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Generalization Bounds for Learning Kernels
Corinna Cortes, M. Mohri, A. Rostamizadeh
2010International Conference on Machine Learning127 citations
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Matrix Coherence and the Nystrom Method
A. Talwalkar, A. Rostamizadeh
2010Conference on Uncertainty in Artificial Intelligence88 citations
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This Time is Different: An Observability Perspective on Time Series Foundation Models
Ben Cohen, E. Khwaja, Youssef Doubli, Salahidine Lemaachi +15 more
2025Neural Information Processing Systems74 citations
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Greedy Column Subset Selection: New Bounds and Distributed Algorithms
Jason M. Altschuler, Aditya Bhaskara, G. Fu, V. Mirrokni +2 more
2016International Conference on Machine Learning74 citations
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Applying WebTables in Practice
S. Balakrishnan, A. Halevy, Boulos Harb, Hongrae Lee +6 more
2015Conference on Innovative Data Systems Research72 citations
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A Survey of Modern Questions and Challenges in Feature Extraction
Dmitry Storcheus, A. Rostamizadeh, Sanjiv Kumar
2015FE@NIPS68 citations
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Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
Shanshan Wu, A. Dimakis, Sujay Sanghavi, Felix X. Yu +4 more
2018International Conference on Machine Learning61 citations
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Multi-Class Classification with Maximum Margin Multiple Kernel
Corinna Cortes, M. Mohri, A. Rostamizadeh
2013International Conference on Machine Learning48 citations
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Stability Bounds for Non-i.i.d. Processes
M. Mohri, A. Rostamizadeh
2007Neural Information Processing Systems47 citations
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Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels
Shuang Song, David Berthelot, A. Rostamizadeh
2019arXiv.org39 citations
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Kernel Learning: Automatic Selection of Optimal Kernels
Corinna Cortes, A. Gretton, Gert R. G. Lanckriet, M. Mohri +1 more
2008Neural Information Processing Systems29 citations
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Learning sequence kernels
Corinna Cortes, M. Mohri, A. Rostamizadeh
200828 citations
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MLSys: The New Frontier of Machine Learning Systems
Alexander J. Ratner, Dan Alistarh, G. Alonso, D. Andersen +65 more
201925 citations
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SysML: The New Frontier of Machine Learning Systems
Alexander J. Ratner, Dan Alistarh, G. Alonso, D. Andersen +62 more
2019arXiv.org23 citations
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Categorical Feature Compression via Submodular Optimization
M. Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu +2 more
2019International Conference on Machine Learning22 citations
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Churn Reduction via Distillation
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter +1 more
2021International Conference on Learning Representations21 citations
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Perceptron Mistake Bounds
M. Mohri, A. Rostamizadeh
2013arXiv.org21 citations
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A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs
A. Rawat, Veeranjaneyulu Sadhanala, A. Rostamizadeh, Ayan Chakrabarti +11 more
2024arXiv.org18 citations
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Scalable and Interpretable Data Representation for High-Dimensional, Complex Data
Been Kim, K. Patel, A. Rostamizadeh, Julie A. Shah
2015AAAI Conference on Artificial Intelligence18 citations Open access
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Is margin all you need? An extensive empirical study of active learning on tabular data
Dara Bahri, Heinrich Jiang, Tal Schuster, A. Rostamizadeh
2022arXiv.org16 citations Open access
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Learning with Missing Features
A. Rostamizadeh, Alekh Agarwal, P. Bartlett
2011Conference on Uncertainty in Artificial Intelligence16 citations
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Ensembles of Kernel Predictors
Corinna Cortes, M. Mohri, A. Rostamizadeh
2011Conference on Uncertainty in Artificial Intelligence14 citations
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Foundations of Coupled Nonlinear Dimensionality Reduction
Dmitry Storcheus, M. Mohri, A. Rostamizadeh
2015arXiv.org13 citations
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Understanding the E ↵ ects of Batching in Online Active Learning
Kareem Amin, Corinna Cortes, Giulia DeSalvo, A. Rostamizadeh
202012 citations
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New Generalization Bounds for Learning Kernels
Corinna Cortes, M. Mohri, A. Rostamizadeh
2009arXiv.org11 citations
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Where to Sell: Simulating Auctions From Learning Algorithms
Hamid Nazerzadeh, Renato Paes Leme, A. Rostamizadeh, Umar Syed
2016ACM Conference on Economics and Computation10 citations
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Learning with Labeling Induced Abstentions
Kareem Amin, Giulia DeSalvo, A. Rostamizadeh
2021Neural Information Processing Systems9 citations
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