Afshin Rostamizadeh

80 papers A* 17A 8B 3Journal 39Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Analyzing Similarity Metrics for Data Selection for Language Model Pretraining. CoRR Dylan Sam, Ayan Chakrabarti, Afshin Rostamizadeh, Srikumar Ramalingam, Gui Citovsky, Sanjiv Kumar
2025	J	`jnl`	This Time is Different: An Observability Perspective on Time Series Foundation Models. CoRR Ben Cohen, Emaad Khwaja, Youssef Doubli, Salahidine Lemaachi, Chris Lettieri, Charles Masson, Hugo Miccinilli, Elise Ramé, Qiqi Ren, Afshin Rostamizadeh, Jean Ogier du Terrail, Anna-Monica Toon, Kan Wang, Stephan Xie, Zongzhe Xu, Viktoriya Zhukova, David Asker, Ameet Talwalkar, Othmane Abou-Amal
2024	J	`jnl`	A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. CoRR Ankit Singh Rawat, Veeranjaneyulu Sadhanala, Afshin Rostamizadeh, Ayan Chakrabarti, Wittawat Jitkrittum, Vladimir Feinberg, Seungyeon Kim, Hrayr Harutyunyan, Nikunj Saunshi, Zachary Nado, Rakesh Shivanna, Sashank J. Reddi, Aditya Krishna Menon, Rohan Anil, Sanjiv Kumar
2024	A*	`conf`	DistillSpec: Improving Speculative Decoding via Knowledge Distillation. ICLR Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
2024	J	`jnl`	No more hard prompts: SoftSRV prompting for synthetic data generation. CoRR Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Afshin Rostamizadeh, Sanjiv Kumar
2024	J	`jnl`	SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection. CoRR Ke Ye, Heinrich Jiang, Afshin Rostamizadeh, Ayan Chakrabarti, Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Gui Citovsky, Sanjiv Kumar
2023	J	`jnl`	DistillSpec: Improving Speculative Decoding via Knowledge Distillation. CoRR Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
2023	A*	`conf`	Leveraging Importance Weights in Subset Selection. ICLR Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang
2023	J	`jnl`	Leveraging Importance Weights in Subset Selection. CoRR Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang
2022	A*	`conf`	Churn Reduction via Distillation. ICLR Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
2022	J	`jnl`	Is margin all you need? An extensive empirical study of active learning on tabular data. CoRR Dara Bahri, Heinrich Jiang, Tal Schuster, Afshin Rostamizadeh
2022	A*	`conf`	Vexation-Aware Active Learning for On-Menu Restaurant Dish Availability. KDD Jean-François Kagy, Flip Korn, Afshin Rostamizadeh, Chris Welty
2021	A*	`conf`	Active Covering. ICML Heinrich Jiang, Afshin Rostamizadeh
2021	J	`jnl`	Active Covering. CoRR Heinrich Jiang, Afshin Rostamizadeh
2021	A*	`conf`	Batch Active Learning at Scale. NeurIPS Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar
2021	J	`jnl`	Batch Active Learning at Scale. CoRR Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar
2021	J	`jnl`	Churn Reduction via Distillation. CoRR Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
2021	A*	`conf`	Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh
2021	A*	`conf`	Learning with Labeling Induced Abstentions. NeurIPS Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh
2020	—	`conf`	A System for Massively Parallel Hyperparameter Tuning. MLSys Liam Li, Kevin Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Jonathan Ben-tzur, Moritz Hardt, Benjamin Recht, Ameet Talwalkar
2020	A*	`conf`	An Analysis of SVD for Deep Rotation Estimation. NeurIPS Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
2020	J	`jnl`	An Analysis of SVD for Deep Rotation Estimation. CoRR Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
2020	J	`jnl`	Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh
2020	A	`conf`	Understanding the Effects of Batching in Online Active Learning. AISTATS Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh
2019	A*	`conf`	Categorical Feature Compression via Submodular Optimization. ICML MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh
2019	J	`jnl`	Categorical Feature Compression via Submodular Optimization. CoRR MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh
2019	J	`jnl`	Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels. CoRR Shuang Song, David Berthelot, Afshin Rostamizadeh
2019	A*	`conf`	Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. ICML Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR 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 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
2019	J	`jnl`	The Practical Challenges of Active Learning: Lessons Learned from Live Experimentation. CoRR Jean-François Kagy, Tolga Kayadelen, Ji Ma, Afshin Rostamizadeh, Jana Strnadová
2018	J	`jnl`	Massively Parallel Hyperparameter Tuning. CoRR Liam Li, Kevin Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, Ameet Talwalkar
2018	J	`jnl`	The Sparse Recovery Autoencoder. CoRR Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2017	J	`jnl`	Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization. J. Mach. Learn. Res. Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
2017	—	`conf`	Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. ICLR (Poster) Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
2016	J	`jnl`	Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits. CoRR Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
2016	A*	`conf`	Greedy Column Subset Selection: New Bounds and Distributed Algorithms. ICML Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam
2016	J	`jnl`	Greedy Column Subset Selection: New Bounds and Distributed Algorithms. CoRR Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam
2016	A*	`conf`	Where to Sell: Simulating Auctions From Learning Algorithms. EC Hamid Nazerzadeh, Renato Paes Leme, Afshin Rostamizadeh, Umar Syed
2015	—	`conf`	A Survey of Modern Questions and Challenges in Feature Extraction. FE@NIPS Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2015	J	`jnl`	An $\tilde{O}(\frac{1}{\sqrt{T}})$-error online algorithm for retrieving heavily perturbated statistical databases in the low-dimensional querying mode. CoRR Krzysztof Choromanski, Afshin Rostamizadeh, Umar Syed
2015	A	`conf`	An Optimal Online Algorithm For Retrieving Heavily Perturbed Statistical Databases In The Low-Dimensional Querying Model. CIKM Krzysztof Marcin Choromanski, Afshin Rostamizadeh, Umar Syed
2015	A	`conf`	Applying WebTables in Practice. CIDR Sreeram Balakrishnan, Alon Y. Halevy, Boulos Harb, Hongrae Lee, Jayant Madhavan, Afshin Rostamizadeh, Warren Shen, Kenneth Wilder, Fei Wu, Cong Yu
2015	J	`jnl`	Foundations of Coupled Nonlinear Dimensionality Reduction. CoRR Dmitry Storcheus, Mehryar Mohri, Afshin Rostamizadeh
2015	—	`conf`	Generalization Bounds for Supervised Dimensionality Reduction. FE@NIPS Mehryar Mohri, Afshin Rostamizadeh, Dmitry Storcheus
2015	A*	`conf`	Scalable and Interpretable Data Representation for High-Dimensional, Complex Data. AAAI Been Kim, Kayur Patel, Afshin Rostamizadeh, Julie A. Shah
2014	B	`conf`	Corporate learning at scale: lessons from a large online course at google. L@S Arthur Asuncion, Jac de Haan, Mehryar Mohri, Kayur Patel, Afshin Rostamizadeh, Umar Syed, Lauren Wong
2014	J	`jnl`	Matrix Coherence and the Nystrom Method. CoRR Ameet Talwalkar, Afshin Rostamizadeh
2014	—	`conf`	Repeated Contextual Auctions with Strategic Buyers. NIPS Kareem Amin, Afshin Rostamizadeh, Umar Syed
2013	—	`conf`	Learning Prices for Repeated Auctions with Strategic Buyers. NIPS Kareem Amin, Afshin Rostamizadeh, Umar Syed
2013	J	`jnl`	Learning Prices for Repeated Auctions with Strategic Buyers. CoRR Kareem Amin, Afshin Rostamizadeh, Umar Syed
2013	—	`conf`	Multi-Class Classification with Maximum Margin Multiple Kernel. ICML (3) Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2013	J	`jnl`	Perceptron Mistake Bounds CoRR Mehryar Mohri, Afshin Rostamizadeh
2012	J	`jnl`	Algorithms for Learning Kernels Based on Centered Alignment CoRR Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2012	J	`jnl`	Algorithms for Learning Kernels Based on Centered Alignment. J. Mach. Learn. Res. Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2012	J	`jnl`	Ensembles of Kernel Predictors CoRR Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2012	—	`book`	Foundations of Machine Learning. Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
2012	J	`jnl`	L2 Regularization for Learning Kernels CoRR Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2012	J	`jnl`	Multiple Source Adaptation and the Renyi Divergence CoRR Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
2011	A	`conf`	Ensembles of Kernel Predictors. UAI Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2011	A	`conf`	Learning with Missing Features. UAI Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett
2011	J	`jnl`	Online and Batch Learning Algorithms for Data with Missing Features CoRR Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett
2010	A*	`conf`	Generalization Bounds for Learning Kernels. ICML Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2010	J	`jnl`	Matrix Coherence and the Nystrom Method CoRR Ameet Talwalkar, Afshin Rostamizadeh
2010	A	`conf`	Matrix Coherence and the Nystrom Method. UAI Ameet Talwalkar, Afshin Rostamizadeh
2010	J	`jnl`	Stability Bounds for Stationary phi-mixing and beta-mixing Processes. J. Mach. Learn. Res. Mehryar Mohri, Afshin Rostamizadeh
2010	—	`—`	Theoretical Foundations and Algorithms for Learning with Multiple Kernels. Afshin Rostamizadeh
2010	A*	`conf`	Two-Stage Learning Kernel Algorithms. ICML Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2009	J	`jnl`	Domain Adaptation: Learning Bounds and Algorithms CoRR Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
2009	A*	`conf`	Domain Adaptation: Learning Bounds and Algorithms. COLT Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
2009	A	`conf`	L2 Regularization for Learning Kernels. UAI Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2009	—	`conf`	Learning Non-Linear Combinations of Kernels. NIPS Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2009	A	`conf`	Multiple Source Adaptation and the Rényi Divergence. UAI Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
2009	J	`jnl`	New Generalization Bounds for Learning Kernels CoRR Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
2008	—	`conf`	Domain Adaptation with Multiple Sources. NIPS Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
2008	—	`conf`	Rademacher Complexity Bounds for Non-I.I.D. Processes. NIPS Mehryar Mohri, Afshin Rostamizadeh
2008	J	`jnl`	Sample Selection Bias Correction Theory CoRR Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh
2008	B	`conf`	Sample Selection Bias Correction Theory. ALT Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh
2008	J	`jnl`	Stability Bound for Stationary Phi-mixing and Beta-mixing Processes CoRR Mehryar Mohri, Afshin Rostamizadeh
2007	B	`conf`	Balancing traffic load in wireless networks with curveball routing. MobiHoc Lucian Popa, Afshin Rostamizadeh, Richard M. Karp, Christos H. Papadimitriou, Ion Stoica
2007	—	`conf`	Stability Bounds for Non-i.i.d. Processes. NIPS Mehryar Mohri, Afshin Rostamizadeh