• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 78 matches

• 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. 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 abs/2401.13160 (2024)
• 
  Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Afshin Rostamizadeh, Sanjiv Kumar:
  No more hard prompts: SoftSRV prompting for synthetic data generation. CoRR abs/2410.16534 (2024)
• 
  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:
  A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. CoRR abs/2410.18779 (2024)
• 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 abs/2301.12052 (2023)
• 
  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
• 
  Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh:
  Churn Reduction via Distillation. ICLR 2022
• 
  Jean-François Kagy, Flip Korn, Afshin Rostamizadeh, Chris Welty:
  Vexation-Aware Active Learning for On-Menu Restaurant Dish Availability. KDD 2022: 3116-3126
• 
  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
• 
  Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
  Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR 2021
• 
  Heinrich Jiang, Afshin Rostamizadeh:
  Active Covering. ICML 2021: 5013-5022
• 
  Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh:
  Learning with Labeling Induced Abstentions. NeurIPS 2021: 12576-12586
• 
  Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar:
  Batch Active Learning at Scale. NeurIPS 2021: 11933-11944
• 
  Heinrich Jiang, Afshin Rostamizadeh:
  Active Covering. CoRR abs/2106.02552 (2021)
• 
  Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh:
  Churn Reduction via Distillation. CoRR abs/2106.02654 (2021)
• 
  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
• 
  Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh:
  Understanding the Effects of Batching in Online Active Learning. AISTATS 2020: 3482-3492
• 
  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
• 
  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)
• 
  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)
• 2019
• 
  MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh:
  Categorical Feature Compression via Submodular Optimization. ICML 2019: 515-523
• 
  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
• 
  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)
• 
  MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh:
  Categorical Feature Compression via Submodular Optimization. CoRR abs/1904.13389 (2019)
• 
  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)
• 
  Shuang Song, David Berthelot, Afshin Rostamizadeh:
  Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels. CoRR abs/1912.00594 (2019)
• 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 abs/1806.10175 (2018)
• 
  Liam Li, Kevin G. Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, Ameet Talwalkar:
  Massively Parallel Hyperparameter Tuning. CoRR abs/1810.05934 (2018)

skipping 48 more matches