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2020 – today
- 2024
[c16]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, Hugh Brendan McMahan, Vinith Menon Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. ICLR 2024- 2023
- [c15]Zheng Xu, Yanxiang Zhang, Galen Andrew, Christopher A. Choquette-Choo, Peter Kairouz, H. Brendan McMahan, Jesse Rosenstock, Yuanbo Zhang:
Federated Learning of Gboard Language Models with Differential Privacy. ACL (industry) 2023: 629-639 - [c14]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. NeurIPS 2023 - [i8]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. CoRR abs/2302.03098 (2023) - [i7]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. CoRR abs/2305.18447 (2023) - [i6]Zheng Xu, Yanxiang Zhang, Galen Andrew, Christopher A. Choquette-Choo, Peter Kairouz, H. Brendan McMahan, Jesse Rosenstock, Yuanbo Zhang:
Federated Learning of Gboard Language Models with Differential Privacy. CoRR abs/2305.18465 (2023) - 2021
- [c13]Galen Andrew, Om Thakkar, Brendan McMahan, Swaroop Ramaswamy:
Differentially Private Learning with Adaptive Clipping. NeurIPS 2021: 17455-17466 - [i5]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth
, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - 2020
- [i4]Swaroop Ramaswamy, Om Thakkar, Rajiv Mathews, Galen Andrew, H. Brendan McMahan, Françoise Beaufays:
Training Production Language Models without Memorizing User Data. CoRR abs/2009.10031 (2020)
2010 – 2019
- 2019
- [i3]Om Thakkar, Galen Andrew, H. Brendan McMahan:
Differentially Private Learning with Adaptive Clipping. CoRR abs/1905.03871 (2019) - 2018
- [i2]Timothy Yang, Galen Andrew, Hubert Eichner, Haicheng Sun, Wei Li, Nicholas Kong, Daniel Ramage, Françoise Beaufays:
Applied Federated Learning: Improving Google Keyboard Query Suggestions. CoRR abs/1812.02903 (2018) - [i1]H. Brendan McMahan, Galen Andrew:
A General Approach to Adding Differential Privacy to Iterative Training Procedures. CoRR abs/1812.06210 (2018) - 2016
- [b1]Galen Andrew:
New Techniques in Deep Representation Learning. University of Washington, USA, 2016 - 2015
- [c12]Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, Emanuel Todorov:
Interactive Control of Diverse Complex Characters with Neural Networks. NIPS 2015: 3132-3140 - 2013
- [c11]Galen Andrew, Raman Arora, Jeff A. Bilmes, Karen Livescu:
Deep Canonical Correlation Analysis. ICML (3) 2013: 1247-1255 - 2012
- [c10]Galen Andrew, Jeff A. Bilmes:
Sequential Deep Belief Networks. ICASSP 2012: 4265-4268 - [c9]Galen Andrew, Jeff A. Bilmes:
Memory-efficient inference in dynamic graphical models using multiple cores. AISTATS 2012: 47-53
2000 – 2009
- 2007
- [c8]Jianfeng Gao, Galen Andrew, Mark Johnson, Kristina Toutanova:
A Comparative Study of Parameter Estimation Methods for Statistical Natural Language Processing. ACL 2007 - [c7]Galen Andrew, Jianfeng Gao:
Scalable training of L1-regularized log-linear models. ICML 2007: 33-40 - 2006
- [c6]Galen Andrew:
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation. EMNLP 2006: 465-472 - [c5]Roger Levy, Galen Andrew:
Tregex and Tsurgeon: tools for querying and manipulating tree data structures. LREC 2006: 2231-2234 - 2005
- [c4]Huihsin Tseng, Pi-Chuan Chang, Galen Andrew, Daniel Jurafsky, Christopher D. Manning:
A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005. SIGHAN@IJCNLP 2005 2005 - 2004
- [c3]Galen Andrew, Trond Grenager, Christopher D. Manning:
Verb Sense and Subcategorization: Using Joint Inference to Improve Performance on Complementary Task. EMNLP 2004: 150-157 - 2003
- [c2]Kevin Leyton-Brown, Eugene Nudelman, Galen Andrew, Jim McFadden, Yoav Shoham:
Boosting as a Metaphor for Algorithm Design. CP 2003: 899-903 - [c1]Kevin Leyton-Brown, Eugene Nudelman, Galen Andrew, Jim McFadden, Yoav Shoham:
A Portfolio Approach to Algorithm Selection. IJCAI 2003: 1542
Coauthor Index
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last updated on 2024-07-30 20:43 CEST by the dblp team
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