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ORCIDAfshin Rostamizadeh
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2020 – today
- 2024
[c39]Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal:
DistillSpec: Improving Speculative Decoding via Knowledge Distillation. ICLR 2024- [i32]Ke Ye, Heinrich Jiang, Afshin Rostamizadeh, Ayan Chakrabarti, Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Gui Citovsky, Sanjiv Kumar:
SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection. CoRR abs/2401.13160 (2024) - 2023
- [c38]Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang:
Leveraging Importance Weights in Subset Selection. ICLR 2023 - [i31]Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang:
Leveraging Importance Weights in Subset Selection. CoRR abs/2301.12052 (2023) - [i30]Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal:
DistillSpec: Improving Speculative Decoding via Knowledge Distillation. CoRR abs/2310.08461 (2023) - 2022
- [c37]Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh:
Churn Reduction via Distillation. ICLR 2022 - [c36]Jean-François Kagy, Flip Korn, Afshin Rostamizadeh, Chris Welty:
Vexation-Aware Active Learning for On-Menu Restaurant Dish Availability. KDD 2022: 3116-3126 - [i29]Dara Bahri, Heinrich Jiang, Tal Schuster
, Afshin Rostamizadeh:
Is margin all you need? An extensive empirical study of active learning on tabular data. CoRR abs/2210.03822 (2022) - 2021
- [c35]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR 2021 - [c34]Heinrich Jiang, Afshin Rostamizadeh:
Active Covering. ICML 2021: 5013-5022 - [c33]Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar:
Batch Active Learning at Scale. NeurIPS 2021: 11933-11944 - [c32]Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh:
Learning with Labeling Induced Abstentions. NeurIPS 2021: 12576-12586 - [i28]Heinrich Jiang, Afshin Rostamizadeh:
Active Covering. CoRR abs/2106.02552 (2021) - [i27]Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh:
Churn Reduction via Distillation. CoRR abs/2106.02654 (2021) - [i26]Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar:
Batch Active Learning at Scale. CoRR abs/2107.14263 (2021) - 2020
- [c31]Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh:
Understanding the Effects of Batching in Online Active Learning. AISTATS 2020: 3482-3492 - [c30]Liam Li, Kevin G. Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Jonathan Ben-tzur, Moritz Hardt, Benjamin Recht, Ameet Talwalkar:
A System for Massively Parallel Hyperparameter Tuning. MLSys 2020 - [c29]Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia:
An Analysis of SVD for Deep Rotation Estimation. NeurIPS 2020 - [i25]Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia:
An Analysis of SVD for Deep Rotation Estimation. CoRR abs/2006.14616 (2020) - [i24]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR abs/2010.05273 (2020)
2010 – 2019
- 2019
- [c28]MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh:
Categorical Feature Compression via Submodular Optimization. ICML 2019: 515-523 - [c27]Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar:
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. ICML 2019: 6828-6839 - [i23]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i22]MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh:
Categorical Feature Compression via Submodular Optimization. CoRR abs/1904.13389 (2019) - [i21]Jean-François Kagy, Tolga Kayadelen, Ji Ma, Afshin Rostamizadeh, Jana Strnadová:
The Practical Challenges of Active Learning: Lessons Learned from Live Experimentation. CoRR abs/1907.00038 (2019) - [i20]Shuang Song, David Berthelot, Afshin Rostamizadeh:
Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels. CoRR abs/1912.00594 (2019) - 2018
- [i19]Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar:
The Sparse Recovery Autoencoder. CoRR abs/1806.10175 (2018) - [i18]Liam Li, Kevin G. Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, Ameet Talwalkar:
Massively Parallel Hyperparameter Tuning. CoRR abs/1810.05934 (2018) - 2017
- [j3]Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar:
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization. J. Mach. Learn. Res. 18: 185:1-185:52 (2017) - [c26]Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar:
Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. ICLR (Poster) 2017 - 2016
- [c25]Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam:
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. ICML 2016: 2539-2548 - [c24]Hamid Nazerzadeh, Renato Paes Leme, Afshin Rostamizadeh, Umar Syed:
Where to Sell: Simulating Auctions From Learning Algorithms. EC 2016: 597-598 - [i17]Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar:
Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits. CoRR abs/1603.06560 (2016) - [i16]Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam:
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. CoRR abs/1605.08795 (2016) - 2015
- [c23]Been Kim, Kayur Patel, Afshin Rostamizadeh, Julie A. Shah:
Scalable and Interpretable Data Representation for High-Dimensional, Complex Data. AAAI 2015: 1763-1769 - [c22]Sreeram Balakrishnan, Alon Y. Halevy, Boulos Harb, Hongrae Lee, Jayant Madhavan, Afshin Rostamizadeh, Warren Shen, Kenneth Wilder, Fei Wu, Cong Yu:
Applying WebTables in Practice. CIDR 2015 - [c21]Krzysztof Marcin Choromanski, Afshin Rostamizadeh, Umar Syed:
An Optimal Online Algorithm For Retrieving Heavily Perturbed Statistical Databases In The Low-Dimensional Querying Model. CIKM 2015: 1381-1390 - [c20]Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar:
A Survey of Modern Questions and Challenges in Feature Extraction. FE@NIPS 2015: 1-18 - [c19]Mehryar Mohri, Afshin Rostamizadeh, Dmitry Storcheus:
Generalization Bounds for Supervised Dimensionality Reduction. FE@NIPS 2015: 226-241 - [i15]Krzysztof Choromanski, Afshin Rostamizadeh, Umar Syed:
An $\tilde{O}(\frac{1}{\sqrt{T}})$-error online algorithm for retrieving heavily perturbated statistical databases in the low-dimensional querying mode. CoRR abs/1504.01117 (2015) - [i14]Dmitry Storcheus, Mehryar Mohri, Afshin Rostamizadeh:
Foundations of Coupled Nonlinear Dimensionality Reduction. CoRR abs/1509.08880 (2015) - 2014
- [c18]Arthur Asuncion, Jac de Haan, Mehryar Mohri, Kayur Patel, Afshin Rostamizadeh, Umar Syed, Lauren Wong:
Corporate learning at scale: lessons from a large online course at google. L@S 2014: 187-188 - [c17]Kareem Amin, Afshin Rostamizadeh, Umar Syed:
Repeated Contextual Auctions with Strategic Buyers. NIPS 2014: 622-630 - [i13]Ameet Talwalkar, Afshin Rostamizadeh:
Matrix Coherence and the Nystrom Method. CoRR abs/1408.2044 (2014) - 2013
- [c16]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Multi-Class Classification with Maximum Margin Multiple Kernel. ICML (3) 2013: 46-54 - [c15]Kareem Amin, Afshin Rostamizadeh, Umar Syed:
Learning Prices for Repeated Auctions with Strategic Buyers. NIPS 2013: 1169-1177 - [i12]Mehryar Mohri, Afshin Rostamizadeh:
Perceptron Mistake Bounds. CoRR abs/1305.0208 (2013) - [i11]Kareem Amin, Afshin Rostamizadeh, Umar Syed:
Learning Prices for Repeated Auctions with Strategic Buyers. CoRR abs/1311.6838 (2013) - 2012
- [b2]Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar:
Foundations of Machine Learning. Adaptive computation and machine learning, MIT Press 2012, ISBN 978-0-262-01825-8, pp. I-XII, 1-412 - [j2]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Algorithms for Learning Kernels Based on Centered Alignment. J. Mach. Learn. Res. 13: 795-828 (2012) - [i10]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Ensembles of Kernel Predictors. CoRR abs/1202.3712 (2012) - [i9]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Algorithms for Learning Kernels Based on Centered Alignment. CoRR abs/1203.0550 (2012) - [i8]Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh:
Multiple Source Adaptation and the Renyi Divergence. CoRR abs/1205.2628 (2012) - [i7]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
L2 Regularization for Learning Kernels. CoRR abs/1205.2653 (2012) - 2011
- [c14]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Ensembles of Kernel Predictors. UAI 2011: 145-152 - [c13]Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett:
Learning with Missing Features. UAI 2011: 635-642 - [i6]Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett:
Online and Batch Learning Algorithms for Data with Missing Features. CoRR abs/1104.0729 (2011) - 2010
- [b1]Afshin Rostamizadeh:
Theoretical Foundations and Algorithms for Learning with Multiple Kernels. New York University, USA, 2010 - [j1]Mehryar Mohri, Afshin Rostamizadeh:
Stability Bounds for Stationary phi-mixing and beta-mixing Processes. J. Mach. Learn. Res. 11: 789-814 (2010) - [c12]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Two-Stage Learning Kernel Algorithms. ICML 2010: 239-246 - [c11]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Generalization Bounds for Learning Kernels. ICML 2010: 247-254 - [c10]Ameet Talwalkar, Afshin Rostamizadeh:
Matrix Coherence and the Nystrom Method. UAI 2010: 572-579 - [i5]Ameet Talwalkar, Afshin Rostamizadeh:
Matrix Coherence and the Nystrom Method. CoRR abs/1004.2008 (2010)
2000 – 2009
- 2009
- [c9]Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh:
Domain Adaptation: Learning Bounds and Algorithms. COLT 2009 - [c8]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Learning Non-Linear Combinations of Kernels. NIPS 2009: 396-404 - [c7]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
L2 Regularization for Learning Kernels. UAI 2009: 109-116 - [c6]Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh:
Multiple Source Adaptation and the Rényi Divergence. UAI 2009: 367-374 - [i4]Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh:
Domain Adaptation: Learning Bounds and Algorithms. CoRR abs/0902.3430 (2009) - [i3]Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
New Generalization Bounds for Learning Kernels. CoRR abs/0912.3309 (2009) - 2008
- [c5]Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh:
Sample Selection Bias Correction Theory. ALT 2008: 38-53 - [c4]Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh:
Domain Adaptation with Multiple Sources. NIPS 2008: 1041-1048 - [c3]Mehryar Mohri, Afshin Rostamizadeh:
Rademacher Complexity Bounds for Non-I.I.D. Processes. NIPS 2008: 1097-1104 - [i2]Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh:
Sample Selection Bias Correction Theory. CoRR abs/0805.2775 (2008) - [i1]Mehryar Mohri, Afshin Rostamizadeh:
Stability Bound for Stationary Phi-mixing and Beta-mixing Processes. CoRR abs/0811.1629 (2008) - 2007
- [c2]Lucian Popa, Afshin Rostamizadeh, Richard M. Karp, Christos H. Papadimitriou, Ion Stoica:
Balancing traffic load in wireless networks with curveball routing. MobiHoc 2007: 170-179 - [c1]Mehryar Mohri, Afshin Rostamizadeh:
Stability Bounds for Non-i.i.d. Processes. NIPS 2007: 1025-1032
Coauthor Index
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