Afshin Rostamizadeh

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 34

Top Topics

Subset Selection

Dimensionality Reduction

Top Venues

Publications

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)
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 (2024)
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 (2023)
Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang
Leveraging Importance Weights in Subset Selection. ICLR (2023)
Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang
Leveraging Importance Weights in Subset Selection. CoRR (2023)
Dara Bahri, Heinrich Jiang, Tal Schuster, Afshin Rostamizadeh
Is margin all you need? An extensive empirical study of active learning on tabular data. CoRR (2022)
Jean-François Kagy, Flip Korn, Afshin Rostamizadeh, Chris Welty
Vexation-Aware Active Learning for On-Menu Restaurant Dish Availability. KDD (2022)
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
Churn Reduction via Distillation. ICLR (2022)
Heinrich Jiang, Afshin Rostamizadeh
Active Covering. CoRR (2021)
Heinrich Jiang, Afshin Rostamizadeh
Active Covering. ICML (2021)
Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR (2021)
Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar
Batch Active Learning at Scale. CoRR (2021)
Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh
Learning with Labeling Induced Abstentions. NeurIPS (2021)
Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar
Batch Active Learning at Scale. NeurIPS (2021)
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
Churn Reduction via Distillation. CoRR (2021)
Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
An Analysis of SVD for Deep Rotation Estimation. CoRR (2020)
Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR (2020)
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)
Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
An Analysis of SVD for Deep Rotation Estimation. NeurIPS (2020)
Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh
Understanding the Effects of Batching in Online Active Learning. AISTATS (2020)
Jean-François Kagy, Tolga Kayadelen, Ji Ma, Afshin Rostamizadeh, Jana Strnadová
The Practical Challenges of Active Learning: Lessons Learned from Live Experimentation. CoRR (2019)
MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh
Categorical Feature Compression via Submodular Optimization. CoRR (2019)
MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh
Categorical Feature Compression via Submodular Optimization. ICML (2019)
Shuang Song, David Berthelot, Afshin Rostamizadeh
Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels. CoRR (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric 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 R. 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 (2019)
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)
Liam Li, Kevin G. Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, Ameet Talwalkar
Massively Parallel Hyperparameter Tuning. CoRR (2018)
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 (2018)
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 (2017)
Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. ICLR (Poster) (2017)
Jason Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. CoRR (2016)
Jason Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. ICML (2016)
Hamid Nazerzadeh, Renato Paes Leme, Afshin Rostamizadeh, Umar Syed
Where to Sell: Simulating Auctions From Learning Algorithms. EC (2016)
Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits. CoRR (2016)
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)
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)
Mehryar Mohri, Afshin Rostamizadeh, Dmitry Storcheus
Generalization Bounds for Supervised Dimensionality Reduction. FE@NIPS (2015)
Dmitry Storcheus, Mehryar Mohri, Afshin Rostamizadeh
Foundations of Coupled Nonlinear Dimensionality Reduction. CoRR (2015)
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 (2015)
Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
A Survey of Modern Questions and Challenges in Feature Extraction. FE@NIPS (2015)
Been Kim, Kayur Patel, Afshin Rostamizadeh, Julie A. Shah
Scalable and Interpretable Data Representation for High-Dimensional, Complex Data. AAAI (2015)
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)
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Repeated Contextual Auctions with Strategic Buyers. NIPS (2014)
Ameet Talwalkar, Afshin Rostamizadeh
Matrix Coherence and the Nystrom Method. CoRR (2014)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Multi-Class Classification with Maximum Margin Multiple Kernel. ICML (3) (2013)
Mehryar Mohri, Afshin Rostamizadeh
Perceptron Mistake Bounds CoRR (2013)
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Learning Prices for Repeated Auctions with Strategic Buyers. CoRR (2013)
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Learning Prices for Repeated Auctions with Strategic Buyers. NIPS (2013)
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
Multiple Source Adaptation and the Renyi Divergence CoRR (2012)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Ensembles of Kernel Predictors CoRR (2012)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Algorithms for Learning Kernels Based on Centered Alignment CoRR (2012)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Algorithms for Learning Kernels Based on Centered Alignment. J. Mach. Learn. Res. 13 (2012)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
L2 Regularization for Learning Kernels CoRR (2012)
Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett
Online and Batch Learning Algorithms for Data with Missing Features CoRR (2011)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Ensembles of Kernel Predictors. UAI (2011)
Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett
Learning with Missing Features. UAI (2011)
Ameet Talwalkar, Afshin Rostamizadeh
Matrix Coherence and the Nystrom Method. UAI (2010)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Two-Stage Learning Kernel Algorithms. ICML (2010)
Ameet Talwalkar, Afshin Rostamizadeh
Matrix Coherence and the Nystrom Method CoRR (2010)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Generalization Bounds for Learning Kernels. ICML (2010)
Mehryar Mohri, Afshin Rostamizadeh
Stability Bounds for Stationary phi-mixing and beta-mixing Processes. J. Mach. Learn. Res. 11 (2010)
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
Domain Adaptation: Learning Bounds and Algorithms. COLT (2009)
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
Multiple Source Adaptation and the Rényi Divergence. UAI (2009)
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
Domain Adaptation: Learning Bounds and Algorithms CoRR (2009)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
New Generalization Bounds for Learning Kernels CoRR (2009)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Learning Non-Linear Combinations of Kernels. NIPS (2009)
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
L2 Regularization for Learning Kernels. UAI (2009)
Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh
Sample Selection Bias Correction Theory. ALT (2008)
Mehryar Mohri, Afshin Rostamizadeh
Stability Bound for Stationary Phi-mixing and Beta-mixing Processes CoRR (2008)
Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh
Sample Selection Bias Correction Theory CoRR (2008)
Mehryar Mohri, Afshin Rostamizadeh
Rademacher Complexity Bounds for Non-I.I.D. Processes. NIPS (2008)
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
Domain Adaptation with Multiple Sources. NIPS (2008)
Lucian Popa, Afshin Rostamizadeh, Richard M. Karp, Christos H. Papadimitriou, Ion Stoica
Balancing traffic load in wireless networks with curveball routing. MobiHoc (2007)
Mehryar Mohri, Afshin Rostamizadeh
Stability Bounds for Non-i.i.d. Processes. NIPS (2007)